Open Collections

UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

An interbattery factor analytic study of relationships between colour vision, ability and personality… Hawkins, John Frederick 1977

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Notice for Google Chrome users:
If you are having trouble viewing or searching the PDF with Google Chrome, please download it here instead.

Item Metadata

Download

Media
831-UBC_1977_A8 H38.pdf [ 5.48MB ]
Metadata
JSON: 831-1.0094141.json
JSON-LD: 831-1.0094141-ld.json
RDF/XML (Pretty): 831-1.0094141-rdf.xml
RDF/JSON: 831-1.0094141-rdf.json
Turtle: 831-1.0094141-turtle.txt
N-Triples: 831-1.0094141-rdf-ntriples.txt
Original Record: 831-1.0094141-source.json
Full Text
831-1.0094141-fulltext.txt
Citation
831-1.0094141.ris

Full Text

INTERBATTBRY FACTOR ANALYTIC STUDY OF RELATIONSHIPS BETUEEN COLOUR VISION, ABILITY AND PERSONALITY VARIABLES by JOHN FREDERICK HAHKINS r B. A., University o f ' B r i t i s h .Columbia,. 1971 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS i n THE FACULTY OF GRADUATE STUDIES Department of Psychology He accept t h i s thesis as conforaing to the required standard THE UNIVERSITY OF BRITISH COLUMBIA September, 1977 © John Frederick Hawkins, 1977 In p r e s e n t i n g t h i s t h e s i s in p a r t i a l f u l f i l m e n t o f the r e q u i r e m e n t s f o r an advanced degree at the U n i v e r s i t y o f B r i t i s h Co lumb i a , I a g ree that the L i b r a r y s h a l l make i t f r e e l y a v a i l a b l e f o r r e f e r e n c e and s tudy . I f u r t h e r agree t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y purposes may be g r a n t e d by the Head o f my Department o r by h i s r e p r e s e n t a t i v e s . It i s u n d e r s t o o d that c o p y i n g o r p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l g a i n s h a l l not be a l l o w e d w i thout my w r i t t e n p e r m i s s i o n . Department or The U n i v e r s i t y o f B r i t i s h Co lumbia 2075 W e s b r o o k P l a c e V a n c o u v e r , C a n a d a V6T 1W.5 Date Sep+ ^ O ^ . i i ABSTRACT A study was conducted to determine (1) whether there were any underlying l i n k s among presently used colour v i s i o n tests, and (2) whether there were any interbattery connections between colour v i s i o n , a b i l i t y and personality variables..156 subjects were tested on four colour v i s i o n tests (the CAT, 100-Hue, BCBT, and P-N anomaloscope, yielding 13 scores), 9 a b i l i t y tests (from the CAB battery), and the 16PF personality test. Maximum likelihood factor analytic technigues were applied to the 13 colour v i s i o n variables. I t was found that two and three factor solutions were useful in explaining r e l a t i o n s h i p s among the 13 colour vision variables; the basic d i s t i n c t i o n i n the two-factor solution being surface colour, s e l f manipulation versus anomaloscope l i g h t , experimenter control while, f o r the three-factor solution, the anomaloscope factor s p l i t into yellow-blue versus red-green and green-blue equations. In the analysis of interbattery relationships (colour vision to a b i l i t i e s and colour v i s i o n to personality), Tucker*s (1958) interbattery factor analytic procedure was used. There was one interbattery colour v i s i o n - a b i l i t y factor that r e l i e d mainly upon a memory element. Two interbattery personality-colour v i s i o n factors were found, one being a reserved, relaxed i n d i v i d u a l who performed better on the surface colour, s e l f manipulated t e s t s and the i i i Other being an aggressive, competitive i n t e l l e c t u a l who performed better on the anomaloscope, l i g h t , experimenter controlled tests. The present findings were compared to previous re s u l t s (Lakowski, 1970b) with no s i m i l a r i t i e s being found, probably due to the difference i n ages of the two populations. Generally, meaningful d i s t i n c t i o n s were made between various colour vi s i o n tasks and underlying connections were demonstrated between colour v i s i o n , a b i l i t y and personality domains. iv TABLE OP CONTENTS abstract i i L i s t of Tables v i acknowledgements v i i Introduction 1 A. Colour Vision 4 B. a b i l i t i e s and Colour Vision 9 C. Personality and Colour Vision 14 D. Colour V i s i o n - A b i l i t i e s - P e r s o n a l i t y 20 E. The Present Investigation 24 Methods 29 Subjects 29 Variables/Tests and Scoring 30 A. Colour Vision 30 B. a b i l i t i e s 34 C. Personality 37 D. .The Colour Pyramid Test 39 administration 44 Analysis Procedure 46 A. Internal Analysis of Colour Vision Tests 46 B. A b i l i t i e s - C o l o u r Vision and Personality-Colour Vision Relationships 48 Results 50 A. The Colour Pyramid Test 52 B. Internal Factor Analysis of Colour Vision Variables 58 C. Interbattery Factor Analysis: Colour Vision and A b i l i t i e s 64 D. Interbattery Factor Analysis: Colour Vision and Personality 64 Discussion 70 A. Internal Analysis of Colour Vision Tests 70 I. Two-Factor Solution 70 II. Three-Factor Solution 72 B. Interbattery Factor Analysis: A b i l i t i e s and Colour Vision 74 C. Interbattery Factor Analysis: Personality and Colour Vision 75 V D. Comparison of Present Findings with Lakowski 0910b) 78 Summary and Concluding Remarks 81 Bibliography 86 Appendix I: Scoring of the Colour Pyramid Test 94 Appendix I I : Colour Pyramid Test Weighted Score Scales 99 Appendix I I I : Correlation Between Age, A b i l i t i e s , Personality and Colour v i s i o n Variables 101 vi LIST OF TABLES Table 1a: Table 1b: Table 2: Table 3: Intercorrelations Among Tests (Lakowski, 1967) Colour Vision Table 4: Table 5: Table 6: Table 7: Table 8: Table 9: Table 10: Table 11: Intercorrelations Among Some Colour Vision Tests (Burnham and Clark, 1955) Interbattery Correlations Among Colour Vision, A b i l i t y , and Personality Variables (Lakowski, 1970b) Variances S p e c i f i c to Each Colour Vision Test and for Values of the Other A b i l i t y and Personality Variables (Lakowski, 1970b) Tests from the CAB Used in the Present Investigation, Time Heguired for Each Test, and the Number of Items Per Test Tests Used, Time Heguired, and Number of Scores Obtained Interbattery Correlations Between CPT Raw Scores, Colour Vision, A b i l i t y and Personality Variables Interbattery Correlations Between CPT Weighted Scale Scores, Colour Vision, A b i l i t y and Personality Variables Internal Analysis of Colour Vision Tests: Oblique Primary Factor Pattern Matrix Interbattery Primary Factor Pattern Matrix: Colour Vision and A b i l i t y Variables Interbattery Primary Factor Pattern Matrix: Colour Vision and Personality Variables Intercorrelations Among Colour Vision and Personality Variables (as per Lakowski, 1970b) 23 25 38 45 53 56 61 65 68 80 v i i ACKNOWLEDGEMENTS After an extended time i n purgatory, t h i s thesis f i n a l l y cane together. For helping to make i t possible, I would l i k e to thank: - Hy advisers. Dr.,R. Lakowski and Dr. A. Ralph Hakstian, for t h e i r guidance and patient assistance. - Jude, for "reminding" me of the date as time passed, but managing to do i t i n a nice way. The many players i n the show who encouraged me when I wanted to pack i t i n . 1 INTRODUCTION In the f i e l d of psychophysics, vi s i o n has probably been more widely studied and intensively investigated than any other perceptual system. S i m i l a r l y , i n the area of i n d i v i d u a l differences the concepts of a b i l i t i e s and personality have intrigued, i n s p i r e d and perplexed psychologists for decades. Oddly enough, when the process of sensory discrimination i s discussed, the effects or roles of personality and a b i l i t y factors are generally minimized or even t o t a l l y ignored. I t i s very rare to f i n d reference to perception as the i n i t i a l step in an information-processing chain in which both personality and a b i l i t i e s play major roles. Sensory discrimination i s usually considered as an information extraction and information coding process that begins at the receptor l e v e l and proceeds through various stages of sophistication and complexity u n t i l i t reaches that area of the brain where the pieces are synthesized into a whole. Investigators i n v i s u a l coding and functioning do not consider, or at least do not dwell on, the p o s s i b i l i t y that the s p e c i f i c a b i l i t y and personality make-up of the i n d i v i d u a l may int e r a c t with the information coding process at various l e v e l s , thus a l t e r i n g i t uniquely f o r that i n d i v i d u a l . In many instances, colour vi s i o n i s relegated to "lower l e v e l " r e t i n a l processes while a b i l i t i e s and personality are given to "higher l e v e l " c o r t i c a l processes. Another perspective on the same problem involves the 2 assumption that we can divide the perceptual process into two stages: (1) the afferent process of sensory input, and (2) the efferent or decision process leading to a response. In a c l i n i c a l colour v i s i o n testing s i t u a t i o n , the f i r s t stage i s the most important and yet one must observe the responses of the patient and therefore must deal with both stages i n the process. The key concept from the above model f o r the present investigation i s stage (2) which incorporates the cognitive component and i s a function of the ob s e r v e r s expectation, motivation, ease in the testing s i t u a t i o n and many other factors.. The implications of a two-stage perceptual process i s that, i f one i s to obtain r e l i a b l e information about the operation of the v i s u a l system from the use of colour vision t e s t s , one must control, as far as possible, any e f f e c t s a r i s i n g from the operation of cognitive components of the t o t a l perceptual process, or else use a method which can i s o l a t e the cognitive component from the sensory component. Lakowski (1968a, 1969, 1970) was one of the very few researchers to recognize and investigate t h i s problem. He suggested that because i t i s very l i k e l y , or indeed necessary, that a given colour task may involve cognitive processes outside the realm of what we narrowly define as colour vision, careful experimental design was needed "which would require information about the colour task, how much of i t depends on the purely psychological make-up of an observer's v i s u a l apparatus, and how 3 much of i t involves elements such as memory, i n t e l l i g e n c e , concept formation, and {occasionally) neuroses" (1968a, p. 5). Burnham, Hanes and Bartleson (1963), i n their book on the basic concepts of colour, b r i e f l y : alluded to the same problem: "Psychological aspects of colour refer to awareness of color, that i s , color responses made by an i n d i v i d u a l when his eyes are stimulated by radiant energy" (p. 12). They refered also to the interactions of these conscious responses with the individual's other conscious responses and behaviour, including such things as attention, memory, motivation and emotion. Unfortunately, t h i s was a l l Burnham et a l . had to say on the subject., Although l i t t l e work has been done on the e f f e c t s of psychological factors in colour vision testing s i t u a t i o n s (with the noteworthy exception of Lakowski's investigation (1970b) which w i l l be discussed in d e t a i l below), i t seems reasonable that these factors could a f f e c t a subject's performance on a colour v i s i o n task to varying degrees as the cognitive aspects of the task are altered. For example, as the cognitive complexity of the testing s i t u a t i o n increases, i t i s probable that the r e l a t i v e importance of i n d i v i d u a l variations i n general i n t e l l i g e n c e or s p e c i f i c a b i l i t i e s w i l l also increase; as the task becomes more complex/ those subjects who possess s p e c i f i c i n t e l l e c t u a l or a b i l i t y c h a r a c t e r i s t i c s relevant to that task w i l l perform that task with greater accuracy. On the other hand, i n an experimental or p r a c t i c a l s i t u a t i o n in which the subject a must discriminate between colours of progressively smaller colour differences, i t i s l i k e l y that the subject*s personality c h a r a c t e r i s t i c s (e.g., anxiety, self-confidence, patience, perseverance) w i l l play an increasingly important role and thus exert a more s i g n i f i c a n t e f f e c t on the subject 1s performance of that task. A. COLOUR VISION Burnham and Clark (1963) defined colour as "an aspect of visual experience that may be referred to scales of hue, saturation, and brightness, comprising a three-dimensional complex apart from s p a t i a l (in different locations) and temporal (successive) aspects of v i s u a l experience" (p. , 5) . Lakowski (1969, p. 179) took t h i s concept a few steps further and said that, i d e a l l y , when colour i s u t i l i z e d i n the context of a test, the "test colour should be confined to the non-spatial, non-temporal attributes of colour perception." They should be further confined to aspects of discrimination susceptible to "least interpretation in terms of past experience and unaffected by i n t e l l i g e n c e or personality.'? However, because of the physical requirements of colour tests, "when colour appears in tests even i n i t s simplest form ... i t i s always at least i n a s p a t i a l and temporal context." The present author suggests that not only i s colour v i s i o n test performance necessarily influenced by the s p a t i a l and temporal contexts of the test colours, but i s further influenced by i n d i v i d u a l i n t e l l i g e n c e 5 and personality contexts. The concept of colour vision i t s e l f as d i s t i n c t from the simple l i n g u i s t i c d e f i n i t i o n i s rather a complex one, and implies a great variety of experiences on the subjective side. Because of t h i s complex interplay of physiological mechanisms and subjective interpretations the terms "colour" and "colour v i s i o n " only become meaningful i f they refer to the end product of an i n t r i c a t e and complex process of perception and interpretation which re s u l t s i n one's conscious awareness of the stimulus or the difference between two s t i m u l i . Because the concept of "colour" i s so complex and multi-faceted, many types of tests are required to assess the various aspects of an individual's colour v i s i o n . One of the most frequent methods of testing colour v i s i o n i s to assess discrimination ( i . e . , to measure d i f f e r e n t i a l thresholds). Several methods can be used to investigate an individual's discrimination a b i l i t i e s : (1) wavelength discrimination {measurement of the d i f f e r e n t i a l thresholds at various wavelengths across the spectrum); (2) hue discrimination (discrimination of non-spectral colours); (3) saturation discrimination [ discrimination of a colour's degree of departure from an achromatic colour (one lacking a distinguishable hue) of the same brightness j ; and (4) anomaloscope data (measurement of the i n t e r v a l of equality or matching range using the p r i n c i p l e of metamerism)., The major 6 d i f f i c u l t y with wavelength discrimination experiments i s that they do not lend themselves to large scale studies because of the prohibitive amount of time needed to acquire s u f f i c i e n t data (to obtain accurate measurements of a subject's discrimination across the v i s i b l e spectrum would take days of experimentation). The l a s t three methods of assessing discrimination mentioned above are much more readily accessible to q u a n t i f i c a t i o n within reasonable time l i m i t s . Each of these areas w i l l be investigated i n the present study, using a s p e c i f i c colour v i s i o n test designed to test that dimension of discrimination ( i . e . , the Farnsworth-Munsell 100-Hue Test, the ISCC Colour Aptitude Test, and the Pickford-Hicolson anomaloscope). (For a more detailed discussion of s p e c i f i c t e s t s , see Methods; Tests and Scoring). In addition to tests of discrimination there are also tests designed to measure s p e c i f i c colour a b i l i t i e s . For example, Burnham and Clark (1954, 1955) designed a s p e c i f i c test of colour memory using hues removed from the context of a configuration. The authors maintained that a l l colour comparisons involve an element of memory with the exception of closely juxtaposed colour matches in small f i e l d s . The present investigation uses Burnham and Clark's Colour Memory Test to measure the s p e c i f i c memory dimension of the subject's colour v i s i o n (see Methods: Tests and Scoring). Although a l l of the above tests commonly investigate colour performance, they do not appear to measure d i f f e r e n t aspects 7 (Lakowski, 1969, 1970) . Lakowski (1967a) did f i n d correlations between some colour v i s i o n tests but only the relationship between the 100-Hue test and the anomaloscope matching range was s t a t i s t i c a l l y s i g n i f i c a n t ( p_ < .01) (see Table 1a). Lakowski concluded (1969) that although a l l colour v i s i o n t e s t s were po s i t i v e l y i n t e r c o r r e l a t e d , "their r e l a t i o n s h i p s are small and not very s i g n i f i c a n t and so i t i s f a i r to assume that each test measures an aspect of colour v i s i o n that the other tests do not.1? S i m i l a r l y , in a study investigating the r e l i a b i l i t y and v a l i d i t y of the i r colour memory test, Burnham and Clark (1955) compared the BCMT with the Wood's Colour Aptitude Test and the ISCC Colour Aptitude Test. Hood's Colour Aptitude Test (SCAT) (Woods, 1952) i s a test of immediate colour memory i n which patterns of one or two colours, varying i n saturation and lightness as well as hue, are presented i n d i v i d u a l l y to the subject. After an i n t e r v a l comparable to that i n the BCMT (5 seconds), the testee selects one (or none) of the four patterns as being i d e n t i c a l in colour appearance to the pattern f i r s t presented. Burnham and Clark found p o s i t i v e correlations between the performance on t h e i r test with that on the two tests of "colour aptitude" (see Table 1b), however, the s t a t i s t i c a l s i g n ificance of the correlations was not discussed. Burnham and Clark concluded that "the uniformly low correlations ... r e f l e c t r e a l differences among the tests and indicate that the three 8 T a b l e l a I n t e r c o r r e l a t i o n s among C o l o u r V i s i o n T e s t s ( L a k o w s k i , 1967a) P-N. anomaloscope ISCC C o l o u r M a t c h i n g Range 100-Hue A p t i t u d e T e s t P-N anomaloscope Matching Range 1.00 100-Uue .60 1.00 ISCC C o l o u r A p t i t u d e T e s t .27 .16 1.00 T a b l e l b I n t e r c o r r e l a t i o n s among Some C o l o u r T e s t s (Burnham and C l a r k , 1955) BCMT ISCC-CAT WCAT BCMT 1.00 -ISCC-CAT .34 1.00 WCAT .42 .39 1.00 9 tests are largely measuring d i f f e r e n t aspects of colour. I t may well be that a general aptitude for colour work i s a function of a number of such s p e c i f i c factors which can only be adequately sampled with a battery of tests.*? (p. 172). B. ABILITIES AND COLOUR VISION Intelligence i s considered by some to be a general a b i l i t y , a common factor i n a wide variety of s p e c i a l a b i l i t i e s (e.g.,Spearman's "g" factor; Spearman, 1927).,, As a general a b i l i t y influencing the development of many s p e c i f i c a b i l i t i e s , i n t e l l i g e n c e may be one of the factors involved i n colour aptitude or discrimination a b i l i t y . For example, in order for a subject to arrange colours i n a hue s e r i e s , he must comprehend the concept of a series. S i m i l a r l y , for an i n d i v i d u a l to communicate to an experimenter the difference between two colours, he must be able to conceptualize that difference and then verbalize i t to the experimenter. In one of the f i r s t studies investigating t h i s intelligence-colour r e l a t i o n s h i p , Pierce (1933,1934) tested 460 colour workers with "normal" colour v i s i o n on a saturation discrimination task. The subjects arranged 16 coloured disks of the same hue but varying saturation into a saturation series for each of three colours: red, yellow, and blue. The r e s u l t s showed a positive c o r r e l a t i o n between i n t e l l i g e n c e , length of colour experience, and colour discrimination a b i l i t y . 10 Another investigation into this i n t e lligence-colour perception r e l a t i o n s h i p was reported by Stroop in 1935. Stroop developed a test involving i n t e l l i g e n c e and interference between colour-usage and word-usage (Stroop Colour Sord Test). The test consists of three cards: a word card (W) ^ a colour card (C), and an incongruous colour-word card (CW). Subjects are required to read the words on the H card and i d e n t i f y the colour patches on the C card. On the CH card, subjects respond with the colour of the ink in which the colour name i s printed rather than reading the word; therefore, the Cw card demands cognitive control i n the face of competing stimu l i . Scores obtained on the t e s t are t o t a l time taken to read each card and number of e r r o r s . Jensen and Bohwer (1966)^ using adult and college age populations, found a tenuous r e l a t i o n between Stroop scores and i n t e l l i g e n c e . Friedman (1971) compared IQ scores to Stroop scores for second-and fifth-grade students and found s i g n i f i c a n t c o r r e l a t i o n s ( g < .01) between i n t e l l i g e n c e and time scores with respect to the H card for second-grade subjects, and the H and CH cards for f i f t h - g r a d e r s . Friedman concluded that i n t e l l i g e n c e must be taken into consideration when the Stroop test i s used with young children. Unfortunately, the Stroop has a major shortcoming i n that there i s no standardized form of the test available i n terms of materials, administration or scoring. Stroop (1935) gave some loose s p e c i f i c a t i o n s for the test i n his introductory paper so that an experimenter wishing to use the test 11 manufactures his own cards from whatever materials he has available, introducing any modifications or a l t e r a t i o n s he thinks necessary., although the research by Jensen and Rohwer (1966), Friedman (1971) and others indicates some tendency for Stroop scores and i n t e l l i g e n c e to be i n t e r r e l a t e d , the gross lack of standardized test products and procedures makes the device inappropriate for the present investigation. This inquiry into possible l i n k s between general in t e l l i g e n c e and colour vis i o n a b i l i t y i s i n t e r e s t i n g but does not reveal any clues as to which s p e c i f i c a b i l i t i e s may be interac t i n g wtih the process of colour perception. Since research findings have d i f f e r e n t i a t e d general i n t e l l i g e n c e into s p e c i f i c a b i l i t y t r a i t s , i t now i s fea s i b l e to determine whether the presence or absence of some par t i c u l a r a b i l i t y w i l l a f f e c t performance on colour v i s i o n tests. Primary mental a b i l i t i e s , now well-established and almost univ e r s a l l y accepted, were f i r s t investigated by Thurstone (1938) and Thurstone and Thurstone (1941)., Further research v e r i f y i n g and extending the l i s t of primary a b i l i t i e s was conducted by C a r r o l l (1943), French (1951), Horn (1968), C a t t e l l (1971), Hakstian and C a t t e l l (1974, 1975) and many others. There i s now no doubt that these are va l i d a b i l i t y constructs that can be assessed by using s p e c i f i c tests or batteries of tests designed for that purpose. , Although very l i t t l e research has been done on the relati o n s h i p between colour v i s i o n variables and s p e c i f i c 12 a b i l i t y dimensions, the recent development of r e l i a b l e measures of s p e c i f i c a b i l i t i e s presents a golden opportunity to investigate such a relationship. It i s plausible that several s p e c i f i c a b i l i t i e s l i s t e d by the above authors might a f f e c t performance on colour v i s i o n tests depending on the r e l a t i v e presence or absence of each of the a b i l i t i e s i n a subject's make-up. One of the few colour perception tests that has been investigated i n r e l a t i o n to a b i l i t i e s i s the Bumham-Clark-Munsell Colour Memory Test (see Method: Tests and Scoring). Hawkins (1973), using s e l f - r e p o r t data from his subjects, found that 87% of his population verbalized colour names while trying to remember the colour chips, employing either a predominant colour system ("blue with a b i t of green") or associating the colour to something within t h e i r personal frame of reference ("the blue of my s h i r t " ) . Using the same colour memory test, Brown and Lenneberg (1954), Lantz and S t e f f l r e (1964) and Lenneberg and Roberts (1956) found that under cert a i n conditions, the subject's colour naming habits a f f e c t colour recognition and colour memory. Lantz and Lenneberg (1966), testing deaf and hearing subjects (usually an i n d i r e c t i n d i c a t i o n of language development) found the e f f e c t of hearing to be s i g n i f i c a n t { £ < «Q5) with the hearing subjects performing better than the non-hearing subjects. To explain t h i s language/colour memory int e r a c t i o n , Lenneberg (1961, 1967) theorized that i t i s the habit of structuring colour material 13 semantically which provides a number of anchoring points in a recognition or r e c a l l task.., The results of Lakowski and Montgomery (1968) with hearing and deaf children do not wholely support the above findings. These authors tested 105 subjects, aged 8 to 16 years (mean=13.8 years), who were c l a s s i f i e d as profoundly deaf (the mean percentage loss for speech frequencies i n the better ear was 95.6%). Testing a population of 30 deaf and 30 hearing subjects on the BCMT, they found no s i g n i f i c a n t difference between hearing boys, deaf boys, or deaf g i r l s but a l l were s i g n i f i c a n t l y d i f f e r e n t from hearing g i r l s who performed best. On the 100-Hue, a test of colour discrimination, they found no s i g n i f i c a n t differences between any of the groups but observed a tendency for high error scores (poorer discrimination) to be more associated with greater mean speech lo s s than low error scores, which seems to suggest an association between speech and colour discrimination. From these findings i t would appear that the more advanced the i n d i v i d u a l ' s verbal a b i l i t y , the more e a s i l y and accurately he can i n t e r n a l l y describe the colour stimulus and therefore make fewer errors i n the memory task. S i m i l a r l y , i f a testee has superior a b i l i t i e s i n s p a t i a l r e l a t i o n s , perceptual speed and accuracy, f l e x i b i l i t y of closure, associative memory, and manual dexterity, these t r a i t s could benefit the testee when he must arrange colours in a series ( i . e . , 100-Hue test), or match a coloured chip to a given series ( i . e . , Colour Aptitude Test) and therefore increase 14 his accuracy at these tasks., (For a more comprehensive description of the a b i l i t i e s and the tests used to assess them i n t h i s study, see Methods: Tests and Scoring)v although relationships between colour v i s i o n factors and s p e c i f i c a b i l i t i e s have been hypothesized, the present author has not found any published research investigating the r e l a t i o n s h i p between s p e c i f i c a b i l i t i e s and colour v i s i o n variables. C. PERSONALITY aND COLOUR VISION Throughout the psychological l i t e r a t u r e , one finds a large number of papers and research a r t i c l e s dealing with personality-colour interactions in terms of information about personality c h a r a c t e r i s t i c s derived from subjects* reactions to colour s t i m u l i . There i s a general consensus about the predominant value of colour, namely that the nature of colour i s more stimulating impulsively and emotionally than i n t e l l e c t u a l l y . Schaie (1966); for instance, divides the main approaches of t h i s personality-colour r e l a t i o n s h i p i n t o three categories: (1) b i o l o g i c a l , (2) esthetic, and (3) symbolic, and discusses the relevant research findings i n each area. These s p e c i f i c findings, however, are of limited a p p l i c a b i l i t y to the present investigation and therefore w i l l not be presented i n d e t a i l . among the more famous and widely-used tests to investigate 15 the association between personality and colour responses are the Colored Rorschach (Rorschach, 1942), The House-Tree-Person Test (Hammer, 1955), the Luscher Colour Test (Luscher, 1948, 1971) and the Colour Pyramid Test ( P f i s t e r , 1950; Schaie and Heiss, 1964). In order for these t e s t s to be v a l i d , two c r i t e r i a must be met: (1) there must be a d e f i n i t e r e l a t i o n s h i p between the testee»s responses to colour and h i s psychopathological status; the response to colour must not occur randomly but i n a consistent manner showing stable and potent associations to the behaviour to be predicted, and (2) the range of i n d i v i d u a l differences i n the colour responses must be s u f f i c i e n t l y large above and beyond these consistencies to permit c l i n i c a l application. Once these c r i t e r i a have been met, implications can be made regarding the subject's emotional state or more general personality t r a i t s from his colour reactions. Judging from the research done on the prediction of personality from colour choices, these two c r i t e r i a have been s a t i s f i e d in many colour preference studies, although to a less r e l i a b l e degree with some tests than with others. when looking at the r e l a t i o n between colour responses and personality, almost a l l of the research has centered on the interaction between a subject's colour preference choices and his personality make-up. Such studies as Odbert, Karwoski, and Ekerson, 1942, Wexner (1954) and Schaie (1961a) have presented subjects with various colours and a l i s t of mood-tones, the 16 subject's task being to match each colour to a mood. These investigations have shown strong c o r r e l a t i o n s between the colour and s p e c i f i c moods for each mood-tone, c e r t a i n colours were chosen to Mgo with" that mood-tone s i g n i f i c a n t l y more often than were other colours. These findings have since been replicated and v e r i f i e d (Hoods, 1956; Schaie, 1966; Birren, 1973) such that certain colour-mood pairs are now considered s u f f i c i e n t l y stable to be considered c e r t a i n t i e s . One of the major d i f f i c u l t i e s with t h i s approach i s that the findings are only consistent for the major colours ( i . e . , red, orange, green, blue, black, white) when they are linked with gross mood-tone scales (exciting-stimulating; distressing-upsetting; calm-peaceful; cheerful-jovial) . Once variations on, or combinations of, these colours or more subtly d i f f e r e n t i a t e d mood-tones are introduced the relationships become les s d i s t i n c t i v e and clear-cut, and may even change e n t i r e l y . One of the t e s t s that attempts to investigate a subject's personality constructs through his choice of colours i s the Colour Pyramid Test ( P f i s t e r , 1950). This t e s t has been used extensively i n Europe since i t s introduction but i t was not u n t i l the 1960's that i t became popular i n North America when Schaie (1961a, 1961b, 1963, 1964) began to e s t a b l i s h North American norms. The Colour Pyramid Test (CPT) i s a test i n which the subject must arrange coloured chips into a pyramid shape to 17 create "pretty" and "ugly" pyramids. Through various weighted scoring systems, the CPT attempts to define basic emotional tendencies as well as their r e l a t i v e strength and weakness i n the personality structure of normal and abnormal subjects. The strength of the CPT l i e s i n the fact that i t i s an objective non-verbal technique with a procedure not involving "introspective s e l f - e v a l u t i o n s " as the subject does not know, and the stimulus structure provides no clues, as to what aspects of his performance w i l l be evaluated and no verbal response i s required. The rationale behind the test i s that the subject w i l l select colours that appeal to him for the "pretty" pyramids and those he d i s l i k e s for the "ugly" ones. The geometric q u a l i t i e s of the pyramid w i l l further influence his s e l e c t i o n to some degree. I t i s f e l t that responses occurring i n such a t e s t w i l l be related to personality dynamics, and thus an analysis of these responses w i l l prove to be helpful i n personality description and diagnosis. The test i s scored on four d i f f e r e n t aspects; (1) the s u b j e c t 1 s d i s t r i b u t i o n of s i n g l e choices; the extent to which a given colour a t t r a c t s his attention or i s avoided by him; (2) the colour combinations the subject selects; (3) the dynamics of the colour process i n which the subject may show consistent or changeable response patterns i n attending to the manyfold s t i m u l i ; and (4) the manner i n which attention i s given to the formal aspects of the pyramid (Schaie and Heiss, 196tt, p.30). 18 In studies investigating the CPT, CMReilley, Holzinger and Blewett (1957) and O'Reilley and Blewett (1959) found that CPT resul t s are independent of variations i n age, sex, and education, and, more importantly for c l i n i c a l a p plications, the CPT successfully d i f f e r e n t i a t e s between schizophrenics and other p s y c h i a t r i c groups tested. S i g n i f i c a n t differences were also found between the performance of normal subjects and schizophrenics, but the CPT showed no capacity to d i f f e r e n t i a t e within the normal group. Burdick (1968) did a comparison of findings on the CPT and the Minnesota Multiphasic Personality Inventory (MMPI) using 50 male subjects between the ages of 17 and 62 years. Burdick found s i g n i f i c a n t p o s i t i v e c o r relations between two colour frequencies and two scales of MMPI variables: (1) the incidence of black i n the CPT, an index of i n h i b i t i o n and blocking, c o r r e l a t i n g with the MMPI K scale, a suppressor variable, and (2) the freguency of the red hue #12 and the MMPI Ma score, a manic scale. Burdick concludes that "while a few personality correlates were found, the construction of the CPT was so questionable that l i t t l e can be concluded from the r e s u l t s " (p. 97). He suggests improvements to the CPT by using new colours to control for unequal saturations and brightnesses, and the unequal freguency of the hues. Schaie and Heiss (1964) tested 100 six to nine year old boys, 100 high-school boys and 100 high-school g i r l s on the CPT 19 and related t h e i r scores to t h e i r IQ (Otis and C a l i f o r n i a Mental Maturity tests) and to their socio-economic status as determined by the father*s occupation. They found no s i g n i f i c a n t correlations between any of the r e l a t i o n s h i p s . I t would appear that there are contradictory results concerning the usefulness of the CPT: i t can d i f f e r e n t i a t e schizophrenics from other psychiatric groups but cannot d i f f e r e n t i a t e within a group of normals, and i t has l i t t l e r e l a t i o n s h i p to any scales on a widely used test of personality assessment (MMPI) . Schaie (1961, 1963, 1966) and Schaie and Heiss (1964) have presented very impressive research findings to demonstrate the v a l i d i t y of the CPT as a device using colour preference as a potent i n d i c a t o r of personality dimensions, but these claims do not seem to be conclusively substantiated by other research (e.g., Burdick, 1968; O'Beilley et a l . , 1957; 0*Reilley and Blewett, 1959). In the present investigation the r e s u l t s from the CPT w i l l be examined i n r e l a t i o n to an assessment of the subject's personality using the 16 PF ( C a t t e l l , Eber and Tatsuoka, 1970). I f the CPT i s a v a l i d d i f f e r e n t i a t o r of s p e c i f i c personality dimensions, t h i s v a l i d i t y should become evident through such an analysis. Although the r e l a t i o n s h i p between colour responses and prediction of personality t r a i t s has been widely investigated (as discussed above), research on the association between colour 20 vision £§rformance and personality i s almost non-existent. Although there seems to be a connection between i n d i v i d u a l colour preferences and personality dimensions, t h i s does not necessarily lead to a l i n k between a subject*s a b i l i t y on colour vision test performance i n an experimental s i t u a t i o n and his s p e c i f i c personality c h a r a c t e r i s t i c s . In f a c t (as stated at the beginning of t h i s introduction), i t i s very rare to find a researcher who studies the p o s s i b i l i t y that as a subject i s performing a colour discrimination task, his s p e c i f i c personality make-up w i l l i n t e r a c t with the process of perception to a l t e r the perception uniquely for that i n d i v i d u a l . I t seems perplexing that one can believe that i n d i v i d u a l colours have a f f e c t i v e value to the i n d i v i d u a l yet not take t h i s into account when the colour i s moved into the context of a discrimination task, but t h i s appears to be what has happened., D. C0LO0H VISION-ABILITIES-PERSONALITY The only study t h i s author has found investigating psychological factors i n colour testing situations i s one by Lakowski (1970b). He was concerned, as i s the present author, with the association between performance on colour v i s i o n tests and performance on tests measuring "cognitive elements and personality variables". On the basis of his experience with these tests, Lakowski discounted the popular assumption that i n t e l l i g e n c e and personality variables do not a f f e c t colour 21 v i s i o n performance. ,• He hypothesizes that some tests present complex colour problems which "might require more i n t e l l i g e n c e or cognitive a b i l i t y (than experimenters believe) and might be affected by personality variations". Lakowski tested 106 Scottish p r i n t e r s 1 apprentices with normal colour v i s i o n (mean age = 15.3 years, s.d. = 9 months), obtaining scores for each subject using pseudo-isochromatic (PIC) plates, the Farnsworth-Munsell 100-Hue te s t , the Pickford-Hicolson anomaloscope, the ISCC Colour Aptitude Test, and Burnham-Clark-Munsell Colour Memory Test.,To assess personality he used the High School Personality Questionnaire (HSPQ) ( C a t t e l l , 1962). This i s the form of the 16PF personality inventory used f o r young adults 12-18 years of age which yie l d s 14 personality t r a i t s and three secondary factors (extraversion, anxiety, neuroticism). To measure i n t e l l i g e n c e he used Haven's Matrices (Raven, 1958) as a measure of abstract i n t e l l i g e n c e ; the Instruction Test SP21 (Vernon and Parry, 1949) which involves following printed i n s t r u c t i o n s consisting of checking the f i l i n g and coding material presented; the M i l l - H i l l Vocabulary Test (Raven and Halshaw, 1944; Raven, 1958) and a standardized form of written essay used at the Applied Psychology Unit which together yielded a composite score of verbal a b i l i t y (Lakowski, 1970, p. 81). Analyses were done on the following: (1) on 106 subjects for a l l tests except the P-N anomaloscope, and (2) on 68 subjects for a l l tests including the 22 P-N anomaloscope. Lakowski found (see Table 2): (1) s i g n i f i c a n t correlations ( £ < .01) between the 100-Hue and BCHT and scores on the cognitive tests (no corre l a t i o n s exceeded .4); (2) no relat i o n s h i p between the cognitive t e s t s and the CAT scale scores, or the cognitive t e s t s and anomaloscope scores (matching ranges and mid-matching points), but some signigicant relationship with CAT t o t a l scores; (3) no s i g n i f i c a n t c o r r e l a t i o n s between the 100-Hue test and the BCMT with any scales of the HSPQ personality test; (4) s i g n i f i c a n t c o rrelations between some personality variables and some CAT and P-N anomaloscope items., For example, the red series on CAT correlated negatively with factor C (ego strength) and factor G (super-ego strength) while the yellow series correlated negatively with factors I (tough-minded), 0 (self-assured) and Neuroticism. (5) s i g n i f i c a n t correlations between personality factors H (shyness) , J (self-doubt), Introversion and Anxiety and v a r i a b i l i t y in anomaloscope mid-matching point f o r the yellow-blue equation; (6) s i g n i f i c a n t c o r r e l a t i o n s between the red-green anomaloscope matching range and personality factor Q3 (controlled), Introversion and Neuroticism; Table 2 Interbattery Correlations between Colour V i s i o n , A b i l i t i e s , and Personality Variables (Lakowski, unpublished paper, 1970) COGNITIVE ELEMENTS U >s o r - l •U u u to 1-1 o u 4J .-f « c w 01 M •H c 01 X I 00 M > < pa 33 PERSONALITY FACTORS SECOND ORDER FACTORS x c o 1-3 2 F-M 100 Hue BCMT o o to Total B R G Y >.01 >.01 .05 >.01 >.01 .05 .02 .05 >.01 .01 .05 .05 .05 .05 .05 .05 MMP O R-G Y-B G-B >.01 .01 .01 .01 o MR R-G < Z I Pi Y-B G-B >.01 >.01 >.0l .05 >.01 >...01 .05 >.01 .05 .05 24 (7) s i g n i f i c a n t correlations between the yellow-blue anomaloscope matching range scores and factors G (conscientious), H (shyness), Q3 (controlled). Introversion and Anxiety, lakowski also determined the amount of variance in the tests "due to s p e c i f i c factors" and the amount due to dimensions that tests have i n common (see Table 3). He found that although the colour v i s i o n tests have some personality or a b i l i t y loadings, " t h i s extraneous variance" (ranging from 4 to 16 percent) " i s r e l a t i v e l y i n s i g n i f i c a n t when compared with the t o t a l for each t e s t " (p. 84). Lakowski concludes that "each of the colour vision tests ... has i t s own independent source of variance" and therefore measures "a t t r i b u t e s s p e c i f i c to i t s e l f " . He surmises (as mentioned e a r l i e r ) that each test i s d i s t i n c t unto i t s e l f i n that i t measures some colour a b i l i t y or aspect of colour perception not assessed by any of the other tests. Because of t h i s independence of function, Lakowski states (p. 85) that "the most i n t e r e s t i n g thing to emerge from t h i s study i s that one test cannot be regarded as a substitute for another." E. THE PRESENT INVESTIGATION The present research i s designed as an extention of the pioneering work begun by Lakowski, some of the tests used being the same and new tests having been added. One d i f f i c u l t y with T a b l e 3 V a r i a n c e s ( i n P e r c e n t a g e s ) S p e c i f i c t o Each C o l o u r V i s i o n T e s t and f o r V a l u e s o f t h e O t h e r V a r i a b l e s ( P o o l e d ) ( L a k o w s k i , 1970, p. 84) VARIANCE w i t h o t h e r S p e c i f i c t o C o l o u r V i s i o n C o g n i t i v e P e r s o n a l i t y T o t a l T e s t T e s t s 100-Hue BCMT CAT B l u e Y e l l o w Green Red 83.9 83.2 93.3 92.9 92.2 87.8 7.6 4.7 1.3 0.8 1.6 4.9 4.4 5.3 0.4 1.2 0.6 0.7 4.0 6.1 4.5 4.9 5.4 4.3 99.9 99.3 99.5 99.8 99.8 97.7 P-N Anomaloscope MMP R-G Y-B G-B 94.5 89. 1 95.8 1.3 1.2 0.8 0.7 1.7 0.9 2.6 8.0 2.1 99.1 100.0 99.6 MR R-G Y-B G-B 87.8 75.3 89.3 6.1 12.3 6.5 1.0 2.0 0.8 4.0 5.2 2.0 98.9 94.8 98.6 L n 26 Lakowski 1s findings i s t h e i r limited a p p l i c a b i l i t y to North American populations since his subjects were Scottish teen-agers. ,It has been demonstrated i n a variety of a b i l i t y and personality dimensions that r e s u l t s from European populations d i f f e r from North American findings i n many aspects, and i t i s possible that these conditions also apply to colour vision r e s u l t s . The major difference between Lakowski's study and the present study i s i n the tests used and the method of assessing the relevant domains. Hhereas Lakowksi obtained 10 colour vision scores, t h i s study w i l l y i e l d 13 scores. The PIC plates w i l l not be used here because of the gross nature of t h e i r colour vision assessment and the ISCC Colour Aptitude scores w i l l be subdivided into an accuracy score for each scale (red, green, yellow and blue) and time taken. The measure of the time taken to complete the task w i l l be used as i t may be influenced by the personality c h a r a c t e r i s t i c s of the i n d i v i d u a l ( i . e . , perserverance, conscientiousness, patience, e t c . ) . The i n t e l l e c t u a l domain, instead of being measured as global i n t e l l i g e n c e , w i l l be divided into 9 separate a b i l i t y dimensions to y i e l d more detailed information about the subject's i n t e l l e c t u a l or a b i l i t y make-up. The a b i l i t i e s chosen for the study are those f e l t to have the highest probability of being i n f l u e n t i a l i n the performance of the colour v i s i o n tasks ( i . e . , verbal, s p a t i a l , perceptual speed and accuracy, associative 27 memory, span memory, numerical, speed of closure, f l e x i b i l i t y of closure, and aiming). The realm of personality w i l l be assessed using the 16PP instead of the HSPQ simply because of the difference i n age between Lakowski's population and the present sample. The Colour Pyramid Test w i l l be added to the test battery as (1) i t i s possible that t h i s method of personality assessment w i l l cross both domains of colour v i s i o n and personality, and (2) to investigate the v a l i d i t y of the CPT as a device for personality evaluation. In addition, a larger sample population w i l l be tested than that used by Lakowski {156 subjects tested on a l l measures as opposed to Lakowski*s t o t a l of 106 with complete analyses ( i . e . , including P-N anomaloscope) on only 68).. This increase in sample si z e w i l l enhance the r e l i a b i l i t y of the r e s u l t s and increase the v a l i d i t y of the s t a t i s t i c a l analyses. The present study w i l l employ more sophisticated s t a t i s t i c a l procedures than those available to Lakowski i n an attempt to further illuminate the re l a t i o n s h i p between the three domains. Factor analyses w i l l be applied to the colour vision r e s u l t s to determine whether there are any underlying l i n k s between the tests or i f each test i s a measure of a separate, s p e c i f i c dimension of colour v i s i o n . , In addition, an interbattery factor analysis (Tucker, 1958) w i l l be applied to the a b i l i t y and colour v i s i o n scores and to the personality and colour v i s i o n scores to uncover any cross battery relationships. 28 To eliminate as many extraneous sources of variance as possible, only male subjects w i l l be tested since major sex differences have been demonstrated on some a b i l i t y and personality dimensions. Fox the same reason, the sample w i l l be as homogeneous as possible with respect to age since the three domains are a l l affected by age variations. 29 METHODS SUBJECTS One hundred eighty-two male college students from the University of B r i t i s h Columbia were tested. They ranged i n age from 17 to 30 years (mean age=20.78 years, standard deviation=2.83). The students were volunteers from undergraduate courses responding to the author's i n - c l a s s requests for subjects. Classes from the Departments of English, Economics, Commerce, Geography, Philosophy, and Psychology were canvassed with the majority of subjects coming from Psychology courses conducted i n the summer and f a l l of 1975. A l l volunteers within the given age range were tested; however, the r e s u l t s for 15 subjects with congenital red-green colour vision d e f i c i e n c i e s were eliminated. Also 11 subjects f a i l e d to complete a l l the tests. Thus, complete analyses were carried out on the remaining 156 subjects.* t i In addition. Armed Forces r e c r u i t s from a Regular O f f i c e r s Training Corps (ROTC) program at Chilliwack, B.C. were almost used as subjects.,Eighty male subjects were ordered to complete a l l testing on a scheduled routine. A l l subjects were group tests on the a b i l i t y and personality tests, and 22 had been colour v i s i o n tested when the sessions were abandoned. It had been found that the r e c r u i t s had no motivation and no desire to do well; t e s t s which normally took 45 to 90 minutes to f i n i s h were consistently completed by the r e c r u i t s i n 15 to 20 minutes with an obvious desire to "get i t over with and get out" as fast as possible. None of the r e s u l t s from t h i s testing were included in the f i n a l analysis. 30 VARIABLES/TESTS AND SCORING A. COLOUR VISION To quantify the subject's colour vision a b i l i t y or colour responses, four tests were used. Two of these tests (the Farnsworth-Hunsell 100-Hue Test, the Pickford-Nicolson anomaloscope) were chosen for t h e i r high r e l i a b i l i t y and v a l i d i t y in diagnosing colour discrimination. The other two tests (the Burnham-Clark-Munsell Colour Memory Test, the Inter-Society Colour Council Colour Aptitude Test) were included to test s p e c i f i c colour s k i l l s . , • • Farnsworth (1943) designed the Farnsworth-Hunsell 100-Hue Test "to measure hue discrimination in a curve of constant value and chroma and thereby indicate the d i s t o r t i o n of the chromaticity plane of anomalous v i s i o n as compared to normal" (p. 568). Its primary uses are, f i r s t , to separate persons with normal colour v i s i o n into classes of superior, average or low colour discrimination a b i l i t y , and second, to measure to zones of colour confusion of colour defective persons (Farnsworth, 1957). The actual t e s t consists of four boxes that together contain 85 moveable caps on which Munsell colours are mounted. Since the subject must arrange these caps i n t o a colour series, the caps are subdivided into four groups of about 21 caps each (red to yellow, yellow to blue-green, blue-green to blue, and blue to purple-red). The colours were selected so as to be 31 equidistant from Illuminant " C , therefore being of equal saturation and brightness. Hue discrimination for surface colours by r e f l e c t i o n i s , therefore, the only variable tested, and i n addition to detecting colour confusion, the test can also indicate minute differences in colour discrimination (Lakowski,1959). The subject receives an error score which i s a measure of the degree of displacement between his arrangement of the colour series and i t s i d e a l arrangement. The v a l i d i t y and r e l i a b i l i t y of the test f o r c l a s s i f y i n g subjects with normal colour vision into good and poor discrimination categories and for detecting the three congenital types of dichromats are high and correlate p o s i t i v e l y with other tests of discrimination (e.g., anomaloscope, wavelength discrimination, pseudo-isochromatic plates) (Lakowski, 1969). For a more detailed description of the apparatus, the colorimetric s p e c i f i c a t i o n s of the caps, and p r o f i l e s and norms, the reader i s directed to Lakowski (1968b, 1969) and Farnsworth (1943). ft f i n e r test of colour discrimination i s possible using the Pickford-Hicolson anomaloscope (Pickford and Lakowski, 1960), a simple colorimeter where a number of colour mixture r a t i o s can be u t i l i z e d for studying both normal and defective colour v i s i o n . The instrument uses f i l t e r e d l i g h t s employing a f i l m mode of appearance. The viewing f i e l d i s b i - p a r t i t e : one-half being standard (one f i l t e r or colour) and the other being 32 variable (involving a mixture of two f i l t e r s ) . On one equation, the c l a s s i c Rayleigh equation, the subject i s presented with a pure yellow l i g h t on the standard half of the f i e l d and a mixture of red and green on the other. The experimenter determines the point at which the subject accepts the two f i e l d s as matching both in colour and brightness. By varying the r a t i o of red to green i n one half of the f i e l d , the experimenter establishes the l i m i t s of the subject's matching range (MR); the smaller the HR, the better the discrimination. , The second eguation involves matchinq a yellow and blue mixture to a neutral; the t h i r d , matching a blue and green mixture to a blue-green. The apparatus units are transformed into just-noticeable-differences (j.n.d.'s); one j.n.d. being the smallest difference between two colours that can be perceived by a normal observer under fixed viewing conditions. From the combined data of matching range and mid-matching point (HHP), inferences can be made about the sensory discrimination and physiology of a subject's vi s u a l system CLakowski, 1969). A more lengthy and i n -depth description of the apparatus, the colorimetric s p e c i f i c a t i o n s for the f i l t e r s , and age norms are available i n Pickford (1957, 1967a, 1967b), Pickford and Lakowski (1960), and Lakowski (1969, 1971). The Burnham-Clark-Munsell Colour Hemory Test (BCHT) (Burnham and Clark, 1954,1955) i s a test of the a b i l i t y to recognize hue or dominant wavelength a short time a f t e r seeing 33 the o r i g i n a l colour; i t i s a direct test of immediate memory for the hue of colours dissociated from the factor of configuration. The test consists of a case enclosing a wheel on which the test chips and comparison chips are mounted. The comparison chips consist of 43 of the odd-numbered hues of the Munsell series (as used i n the 100-Hue Test described above). Duplicates of 20 of the hues are used as the test chips and duplicates of a further 2 hues are used as practice chips. The test and comparison chips are mounted on two concentric c i r c l e s on a f r e e l y rotating wheel. The subject i s presented with one test hue f o r 5 seconds and a f t e r a retention i n t e r v a l of 5 seconds, he i s reguired to select from the range of comparison chips the one which matches the f i r s t hue shown. This procedure i s repeated f o r the 20 test hue chips and the subject i s given an error score on the accuracy of his memory choices; the lower the score, the more accurate his matches. Further d e t a i l s on the t e s t , i t s r e l i a b i l i t y and norms can be found i n Burnham and Clark (1954, 1955), Lakowski (1969), and Lakowski and deBeck (1973) . The Inter-Society Colour Council Colour Aptitude Test (ISCC-CAT) (Dimmick, 1946,1956) was designed to test innate and acquired colour vi s i o n s k i l l s , e s s e n t i a l l y to test the a b i l i t y to discriminate small differences i n saturation at four points i n the colour space when hue i s held constant. Dimmick found that matching judgements made within saturation series of f i n e l y graded steps gave a well d i s t r i b u t e d set of i n d i v i d u a l scores 34 upon which to e s t a b l i s h "colour matching aptitude ratings" (1946, p.21). The test consists of moveable and immoveable coloured chips. Forty-eight immoveable chips are afixed to a panel i n four horizontal rows (blue, green, red and yellow) arranged randomly within the d i f f e r e n t hue saturations. The corresponding 48 moveable chips, i n a s p e c i f i c random order, are kept i n a p l a s t i c dispenser which presents one chip at a time.,. The colour task consists of matching the i n d i v i d u a l chips from the dispenser, one at a time, with the corresponding ones on the board. The matches are not scored simply as " r i g h t " or "wrong", but are weighted such that a correct match gets the highest score (3) and a near match (a match made to a neighbouring chip i n the series) gets p a r t i a l c r e d i t (2 or 1). Each subject receives an accuracy score for each of the four s e r i e s , a t o t a l accuracy score (the sum of the four s e r i e s ) , and the t o t a l time taken to complete the test i s recorded. B. ABILITIES To obtain scores on the subject's i n t e l l e c t u a l a b i l i t i e s (in the form of primary mental a b i l i t i e s ) , the Comprehensive A b i l i t i e s Battery (CAB) (Hakstian and C a t t e l l , 1975) was used. The CAB was designed to "provide a broad battery of short tests, so as to furnish investigators with an economical vehicle for assessing a wide range of important a b i l i t y constructs" (p. 3). Two p r i n c i p l e s were rigourously maintained i n the construction 35 of items for the CAB t e s t s : (1) the items had to be c l e a r l y i d e n t i f i e d - from both e a r l i e r research and that accompanying the development of the CAB - with the appropriate a b i l i t y factor; and (2) the items had to be independent of a l l other factors except those they were designed to measure (p.4). Of the 20 tests i n the CAB, the nine u t i l i z e d in t h i s research were (pp. 5-6): (1) Verbal (V): This refers to the comprehension of words and ideas, to a person's a b i l i t y to understand written language. In the CAB, V i s assessed by two d i f f e r e n t kinds of items: (a) vocabulary and (b) understanding proverbs. (2) Numerical (N): This refers to the f a c i l i t y to manipulate numbers, guickly and accurately, i n tasks involving addition* subtraction, m u l t i p l i c a t i o n , d i v i s i o n , squaring, dealing with f r a c t i o n s , etc.. (3) S p a t i a l (S): This a b i l i t y i s concerned with perceiving s p a t i a l patterns accurately, and following the orientation of figures when t h e i r position i n a plane or space i s altered. In the CAB S i s assessed by items i n which the examinee must be able to determine guickly whether simple two dimensional figures have been rotated into new positions or i f they have been f l i p p e d over into new positions. (4) Speed of Closure (Cs): This refers to the a b i l i t y to see 36 quickly a whole stimulus when parts of i t are missing, or to "complete the ges t a l t " . , Cs i s assessed i n the CAB by items i n which the examinee must look at a "mutilated word" < a word with parts of the l e t t e r s missing), decide what the word i s , and f i n d which one of the f i v e scrambled choices has the correct l e t t e r s to s p e l l the incomplete word. (5) Perceptual Speed and Accuracy (P): This perceptual a b i l i t y i s concerned with making rapid evaluation of features of v i s u a l s t i m u l i . In the CAB tes t of t h i s a b i l i t y , the examinee must rapidly evaluate the sameness or difference of paired groups of l e t t e r s or numbers., (6) F l e x i b i l i t y of Closure (Cf): This involves penetrating or disregarding i r r e l e v a n t stimulus material i n a perceptual f i e l d to find key stimulus figures. Cf i s assessed i n the CAB by the "hidden-figures" design i n which the s p e c i f i c figure i s embedded within a more complex design. (7) Associative Memory (Ma): This i s the a b i l i t y to r e c a l l material learned i n a non-meaningful, or rote, manner. In the CAB test of Ma, the examinee has to r e c a l l previously studied design^number pairs i n which no meaningful mediating l i n k i s present. (8) Memory Span (Ms) : This involves c l a s s i c short-term memory. 37 In the CAB test of Ms, strings of d i g i t s , varying i n length from f i v e to ten d i g i t s , are a u d i t o r i l y presented from a tape; the examinee must reproduce the strings immediately aft e r they have been presented. <9) Aiming (A): This a b i l i t y refers to the carrying out of precise movements requiring rapid eye-hand coordination..The A test requires the examinee to draw f i n e l y controlled p e n c i l l i n e s , as quickly as he can, i n s p e c i a l l y constructed figures., The number of items per t e s t and tes t i n g times are given in Table 4. Scores on the above a b i l i t y factors were obtained using the number of correct responses; no correction for chance was applied. C. PERSONALITY In terms of administration time and amount of information obtained, one of the best tests for assessing personality t r a i t s i n the present study was f e l t to be C a t t e l l ' s 16 Personality Factor Questionnaire { c a t t e l l , Eber and Tatsuoka, 1970).As t h i s test i s well-known and extensively documented, time w i l l not be spent on a lengthy description. Generally, the 16PF i s administered to subjects 16 years of age or older, yieldi n g 16 primary factor scores: sizothymia vs 38 Table 4 Tests from the CAB Used i n the Present Investigation, Time Required f o r Each and Number of Items Per Test Test Working Time* (minutes) Number of Items Verbal (V) Part I 3.75 14 Part II 2.50 6 Numerical (N) 5.50 20 S p a t i a l (S) 4.50 72 Speed of Closure (Cs) 5.00 20 Perceptual. Speed and Accuracy (P) 4.50 72 F l e x i b i l i t y of Closure (Cf) 5.00 12 Associa t i v e Memory (MA) Study L i s t 3.50 Test 2.50 14 Memory Span (Ms) 10.00 + 75 Aiming (A) Part I 2.50 35 Part II 2.50 35 TOTAL 51.75 375 This i s act u a l t e s t i n g time, not including i n s t r u c t i o n s , etc. 'lime i s approximate since t h i s test i s e n t i r e l y on tape. (FROM: Hakstian and C a t e l l , 1975) 39 a f f ectot hymia or reserved vs outgoing (A), l e s s i n t e l l i g e n t vs more i n t e l l i g e n t (B), ego weakness vs ego strength or affected by feelings vs emotionally stable (C), submissiveness vs dominance or humble vs assertive (E),- desurgency vs surgency or sober vs happy-go-lucky (F) , superego strength or expediency vs conscientious (G) , t h r e c t i a vs parmia or shy vs venturesome (H), harria vs premsia or tough-minded vs tender-minded (I) , al a x i a vs protension or trusting vs suspicious (L) , praxernia vs autia or p r a c t i c a l vs imaginative (M), naivete vs shrewdness <N), untroubled adequacy vs g u i l t proneness or self-assured vs apprehensive (0)7 conservative vs experimenting (Q1)> group dependency vs s e l f - s u f f i c i e n c y (Q2), undisciplined s e l f - c o n f l i c t vs controled, high strength of self-sentiment (Q3) , and low vs high ergic tension or relaxed vs tense (QA). In the present study. Form A of the 16PF^ containing 374 items, was used. Scores on the personality factors were obtained according to the standard procedure described i n the manual usinq scorinq s t e n c i l s and norm charts ( C a t t e l l , Eber and Tatsuoka, 1970). D. THE COLOUR PYRAMID TEST The Colour Pyramid Test (CPT) was developed by P f i s t e r i n 1950 and had received wide acceptance throuqhout Europe before Schaie introduced i t to North America i n the 1960*s and began to c o l l e c t norms for American population samples^ The strength of 40 the test l i e s in i t s method of assessment: i t i s an objective, non-verbal technique which evaluates the subject's personality structure through his colour preference., The test materials consist of coloured chips of 24 d i f f e r e n t hues (15 chips of each hue). The subject i s presented with the pyramid structure ( see Appendix I) and instructed to chose from the 360 hue chips any 15 so as to f i l l the spaces i n the pyramid structure. The subject i s f i r s t asked to construct the " p r e t t i e s t " pyramid that he can, r e v i s i n g his scheme as often as he wishes u n t i l he i s s a t i s f i e d . , Hhen t h i s i s accomplished, the examiner records the number of the hues used in each position, returns the used hues to t h e i r container and again asks the subject to construct the " p r e t t i e s t " pyramid that he can which may be either the same as or di f f e r e n t than i his f i r s t "pretty" pyramid. This continues u n t i l the subject has constructed 3 "pretty" pyramids and the procedure i s repeated with the subject constructing 3 "ugly" pyramids. Various scores (raw and arithmetic sums) on the GPT are calculated to y i e l d information on those aspects of personality which are relevant to a f f e c t expression and impulse control. Schaie and Heiss (1964), i n their manual on the CPT, d i f f e r e n t i a t e d various scoring schemes which would yield measures on d i f f e r e n t aspects of the i n d i v i d u a l * s personality (see Appendix I ) : (1) for each of the 24 d i f f e r e n t hues, a d i s t i n c t set of behavioural correlates i s proposed; (2) a 41 simpler, more i n f e r e n t i a l system of these correlates i s based on the 10 colour scores; (3) colour syndrome scores; (4) sequence formulae scores; and (5) regression equations that weight each of the above scores to give a subject's placement on bipolar behavioural ratings. For each subject, the above measures are taken for both the pretty and the ugly pyramids. Because the procedure of using each of the 24 d i f f e r e n t hues ( i . e . , 4 reds, 2 oranges, 2 yellows, 4 greens, 4 blues, 3 purples, 2 browns, 1 white, 1 grey, 1 black) involves a tremendous time consideration in terms of scoring and analysis, and the information obtained i s no more useful that that obtained from the 10 colour scores ( i . e . , red, orange, yellow, green, blue, purple, brown, white, grey, black), the 10 colour scores were used i n the present analysis as i n d i c a t o r s of the potential behavioural correlates for the i n d i v i d u a l colours. The 'colour syndrome* y i e l d s 4 scores which are indications of the subject's choices of s p e c i f i c colours i n combination (see appendix I ) . although i t i s possible to form a large variety of such colour combinations, Schaie and Heiss (1964) state that certain combinations were chosen because of t h e i r particular i n t e r p r e t i v e s i g n i f i c a n c e . The f i r s t colour syndrome score, a sum of red, orange and yellow, i s c a l l e d the stimulation syndrome (S) and indicates the individual's mood state or l e v e l of a f f e c t i v e arousal. On t h i s scale, a high S score shows elat i o n while a low score indicates depression. The second 42 scale, a sum of red, green and blue, i s the normal syndrome (N) and i s a measure of psychic balance or the subject's use of t y p i c a l mechanisms of affect regulation. On t h i s dimension, a high score refers to overcontrolled or constricted personalities while a low score refers to a loosening of controls and f l u i d i t y of defences. The t h i r d scale i s the achromatic syndrome (A) and i s arrived at by summing black, white, and grey. This syndrome i s a guide to c l i n i c a l and withdrawal tendencies where a high score i l l u s t r a t e s inadequate character development, ego weakness and neurotic tendencies, while a low score contains the opposite tendencies. The f i n a l colour syndrome, the drive syndrome (D), a sum of green, yellow and brown, i s a measure of the energy l e v e l and i s almost i d e n t i c a l to C a t t e l l * s s u r g e n c y factor. On thi s scale, a high score refers to high energy l e v e l s and the a b i l i t y to invest i n productive a c t i v i t y while a low score indicates low energy l e v e l s and asthenic response patterns., The sequence formulae scores are measures of the subject*s tendency to attend to or avoid certain colours, to choose or to avoid such colours consistently, and to s h i f t h is attention from certain colours to others.. The four sequence scores are {see Appendix I ) : {"0 constant sum (CS) , a measure of how many colours a subject uses i n a l l three of his pyramids or how constant the subject i s i n h i s colour choice; {2) the sum of minimal change (MiS), an indicator of how many colours the subject uses i n two of the three pyramids; (3) sum of maximal 43 change (HaS), a s p e c i f i c a t i o n of the number of colours the examinee chooses i n one of the three pyramids only; and (4) avoidance sum (AS), an assessment of the colours which the subject does not use i n any of his pyramids. F i n a l l y , Schaie and Heiss (1964) obtained regression equations (in t h i s case discriminant functions since the scales are dichotomous) l i n k i n g scores on the CPT with behaviour ratings on the 42 bipolar t r a i t s contained i n C a t t e l l r s (1957) "normal t r a i t sphere" based on c l a s s i f i c a t i o n s made by classroom and guidance teachers for t h e i r pupils (a l i s t of these 42 dimensions i s given i n Appendix IT) ./Unfortunately the only normative data available for an adult population are those based on German adults and, for North American subjects, the highest age norms are for 15 to 18 year old males (N=100). For the present study, the regression weights given for the 15 to 18 year old North American males were used to obtain each subject's placement on the 4 2 scales. One method of scoring proposed by the authors of the manual i s the form l e v e l score which represents the subject's degree of attention paid to the s t r u c t u r a l aspects of the pyramid. According to t h i s method, the experimenter decides whether the pyramid i s constructed according to colour dominance (3 types), colour separation (4 types), or s t r u c t u r a l dominance (4 types). The major disadvantage to t h i s procedure i s the great degree of s u b j e c t i v i t y introduced as the experimenter attempts to 44 determine which of the 11 types of structures the subject has employed. Because of the necessity f o r subjective in t e r p r e t a t i o n , t h i s method of scoring was not u t i l i z e d i n the present study., Most of the reported r e l i a b i l i t y studies on the CPT (Schaie, 1963; Schaie and Heiss, 1964) use tes t - r e t e s t methods. The r e l i a b i l i t y c o e f f i c i e n t s are, on the average, .60 which i s approximately egual to most other widely^-used personality tests. Internal consistency was studied by Schaie (1963) who administered the CPT to a group of 43 delinquent g i r l s i n a state t r a i n i n g school. He used analysis of variance to estimate i n t e r n a l consistency and obtained an o v e r a l l c o e f f i c i e n t of .74. ADMINISTRATION The tests were administered to subjects i n two parts: a group testing s i t u a t i o n for the CAB and the 16PF and an ind i v i d u a l testing s i t u a t i o n for the colour vision tests and the Colour Pyramid Test. The group test took approximately two hours (see Table 5 for times of each t e s t ) . Subjects were f i r s t given a br i e f explanation of the nature of the tests and the time involved. The nine a b i l i t y t e sts from the CAB were then administered, taking approximately one hour (see Table 5). After a short rest break the subjects completed the 16PF at t h e i r own pace (which usually took between 45 and 90 minutes) subjects were tested in Table 5 Tests Used, Times Required and Number of Scores Obtained Time Number of Tests (minutes) Scores CAB 70 9 16PF 60 16 Colour v i s i o n : - 100-Hue 20 1 - Colour Memory 25 1 - Colour Aptitude 60 5 - Anomaloscope 20 6 Colour Pyramid 20 78 TOTAL 275* 116 Time for group t e s t i n g = 130 minutes Time f or i n d i v i d u a l t e s t i n g = 145 minutes 46 groups ranging in s i z e from 5 to 25 subjects with a l l sessions being administered by the author. Subjects were informed that they were free to discontinue with the experiment at any time should they so desire. The colour v i s i o n tests were i n d i v i d u a l l y administered at the subject's convenience i n the Visual Laboratory of the Psychology Department at the University of B r i t i s h Columbia. The 100-Hue, Colour Memory, Colour Aptitude, and Colour Pyramid tests were administered under a Macbeth '-C illuminant {647QQK) which simulates daylight with a northern exposure. The Pickford-Nicolson anomaloscope; because i t requires extensive t r a i n i n g and practice to obtain consistent, r e l i a b l e r e s u l t s , was administered by Ms. Adele Morton, who was fa m i l i a r with the apparatus and competent i n extracting v a l i d r e s u l t s on the instrument. A l l other tests were administered by the author. ANALYSIS PRODECU8E A. INTERNAL ANALYSIS OF COLOUR VISION TESTS Although only subjects with "normal" colour perception were included in the main analyses, the population sampled did exhibit vast i n d i v i d u a l differences on the colour v i s i o n as well as personality and a b i l i t y tests. I t i s only to the extent to which subjects exhibit i n d i v i d u a l differences in a process that these differences become accessible to investigation by 47 f a c t o r i a l methods. Such a range of in d i v i d u a l differences as shown i n the present population lends i t s e l f i d e a l l y to a f a c t o r i a l analysis for possible underlying relationships between tests. "Factor analysis has become the generic term f o r a variety of procedures developed for the purpose of analysing the int e r c o r r e l a t i o n s within a set of variables" (Cooley and Lohnes, 1971, p.129). For analysing the structure of covariance or correlation matrices, two methods that formally resemble each other, but have rather d i f f e r e n t aims, are currently i n use. One i s p r i n c i p a l component analysis, developed by Pearson and Hotelling; the other i s factor analysis, which originated with the work of Spearman and was modified by Thurstone. , P r i n c i p a l component analysis i s useful whenever the task i s to determine the minimum number of independent dimensions needed to account for most of the variance in the o r i g i n a l set of variables. In t h i s procedure, "a set of p variates, denoted by X(1) ... X(p) i s transformed l i n e a r l y and orthogonally into an equal number of new variates, Y{1) ... Y(p) that have the property of being uncorrelated. These are chosen such that Y{1) has maximum variance, ¥{2) has maximum variance subject to being uncorrelated with Y{1) and so on" (Lawly and Haxwell, 1971, p. 2) . In contrast to the method of p r i n c i p a l components, the aim of factor analysis i s to account for the covariances of the 48 observed variates i n terms of a much ; smaller number of hypothetical variates, or factors. This analysis i n t e r c o r r e l a t e s test measures to determine the number of dimensions the test space occupies, and to i d e n t i f y these dimensions i n terms of general concepts or underlying t r a i t s . By observing which tests f a l l on a dimension, one can then investigate their i n t e r r e l a t i o n s and i n f e r what the t e s t s have i n common that i s missing from tests which do not f a l l on the dimension. These s t a t i s t i c a l methods, when applied to the 13 colour vision variables, w i l l reveal any e x i s t i n g relationships between the te s t s ; that i s , they w i l l demonstrate whether some of the colour v i s i o n tests share some underlying p r i n c i p l e s or whether each test (or tests) i s t e s t i n g some aspect of perception which i s unique unto i t s e l f . B. ABILITIES-COLOUR VISION AND PERSONALITY-COLOUR VISION RELATIONSHIPS .There are a number of procedures for the simultaneous examination of two sets of variables, one of which i s interbattery factor analysis. This procedure (Tucker,1958) i s a method for establishing f a c t o r s which can be hypothesized to account for cross-battery r e l a t i o n s h i p s . Since the factoring procedures are applied only to the P x Q cross-battery c o r r e l a t i o n matrix (P = number of variables i n the f i r s t battery, Q = the number of variables in the second battery), the 49 obtained factors underlie only the cross c o r r e l a t i o n s , and not the within-battery c o r r e l a t i o n s f o r each battery (Hakstian and C a t t e l l , 1977). Using these procedures, i t w i l l be established which, i f any, t r a i t s underlie both domains involved, l i n k i n g them together at some deeper, more abstract l e v e l . 50 .RESULTS Before the primary analyses could be i n i t i a t e d , modifications to the data were necessary..Specifically, some colour vi s i o n scores had to be transformed into accuracy scores i n order to ensure consistent scaling procedures such that low scores would indicate poor performance and high scores good performance. The transformations do not a l t e r the nature of the data, and are simply applied so that a l l scores are i n the same sca l i n g form. as the CAT scores were already i n an accuracy form, they were not transformed. However, the 100-Hue scores and the BCHT scores were i n error score form; the higher the score, the more errors., To be consistent with accuracy scores, the error score f o r the 100-Hue was subtracted from 150 and the error score for the BCHT was subtracted from 50, these maximum values being high enough that no negative accuracy scores were obtained. / Two conversions were applied to the anomaloscope data i n order to convert them to the same scaling form. The matching ranges (HR) for each of the three equations were subtracted from 75 f o r each subject. , Because of d i r e c t i o n a l i t y problems with mid-raatchinq points {HHP) , a more elaborate manipulation was necessary for t h i s conversion. For example, i f the mean "normal" HHP f o r the red-green equation i s 50 [ on a scale from 0 (green) to 100 (red)], then two subjects who have HHP*s of 40 and 60 are equally deviant from the mean but deviate i n opposite 51 d i r e c t i o n s . Although information about the d i r e c t i o n of deviation i s important i n terms of evaluating colour mechanism functioning, i t i s misleading i n terms of quantifying the absolute deviation of each subject. In a s t a t i s t i c a l a n a l y s i s , scores of 40 and 60 usually represent differences i n the quality of the performance whereas, i n practice, these scores are equally good or bad. Because of t h i s d i f f i c u l t y , the mean MMP for the 156 "normal" subjects was calculated and t h i s mean was considered the "normal MM P". Each subject»s score was then subtracted from the mean MMP for that equation (for the red-green equation, the mean MMP was 55.5, f o r the yellow-blue i t was 52.7, and for the green-blue i t was 50.7) to determine his degree of deviation. The subjects* MMPs were then i n error score form (the smaller difference s i g n i f i e d the smaller deviation from the mean and therefore the better discrimination, and vice versa), therefore to convert them to accuracy scores, each subject's score was subtracted from 40. The transformation of a l l colour vision r e s u l t s to accuracy scores yielded p o s i t i v e scores for the subject*s performance and f a c i l i t a t e d the task of analysis and in t e r p r e t a t i o n of the findings. Fortunately, these score conversions were not necessary for the other tests used. The CAB subtest scores were already i n accuracy form so these remained unchanged. Since the 16PF scores were on bipolar dimensions, the transformations were not applicable. The CPT scores did not have an accuracy score 52 equivalent so the scores were used as described i n Methods: Tests and Scoring above. as a f i r s t step i n the analysis, Pearson product-moment co r r e l a t i o n s were calculated and studied to determine whether additional analyses would be necessary to investigate previously unexpected findings, or whether any of the three major planned analyses [ (1) i n t e r n a l factor analysis of the colour vision tests, <2) inter b a t t e r y factor analysis of a b i l i t i e s and colour v i s i o n , and (3) interbattery factor analysis of personality and colour v i s i o n ] were c l e a r l y not j u s t i f i e d . (The correlations between the 13 colour v i s i o n , 9 a b i l i t y , and 16 personality variables are presented i n Appendix I I I , the CPT variables being excluded for reasons discussed below.) The corr e l a t i o n c o e f f i c i e n t s did not reveal any unexpected interactions that would necessitate additional analyses. The c o e f f i c i e n t s also suggested that l i n k s may exist between the three domains of colour v i s i o n , a b i l i t i e s and personality, and as these would be c l a r i f i e d by factor a n a l y t i c techniques, the three planned analyses were carried out. A. THE COLOUR PYRAMID TEST When corr e l a t i o n s between the CPT raw scores (36 scores) and the colour v i s i o n , a b i l i t i e s , and personality;variables were studied, the r e s u l t s were very discouraging. Table 6 shows the relevant interbattery correlations between the CPT and the other Table 6 Interbattery Correlations Between Colour Pyramid Test (CPT) Raw Scores and Other Variables (a) CPT Raw Scores and Colour V i s i o n (b) CPT CPT Raw Scores Colour V i s i o n Correlations Freq Blue (pretty) Time (CAT) -.21 Freq Blue (pretty) 100-Hue -.21 Freq Black (pretty) GBMR -.25 Freq Brown (pretty) BCMT + .20 Freq Black (pretty) GBMMP -.20 Cs Seq (pretty) YBMMP -.20 f Raw Scores and CAB CPT Raw Scores >:CAB Correlations Freq Black (pretty) V -.26 .20 out of 504 .20 out of 324 These are the only c o r r e l a t i o n s where .20 < £ < -co r r e l a t i o n s . These are the only c o r r e l a t i o n s where .20 < r_ < -co r r e l a t i o n s . 54 Table 6 (continued) * (c) CPT Raw Scores and 16PF CPT Raw Scores 16PF Correlations Freq Yellow (ugly) Freq Brown (ugly) Freq White (pretty) A B I -.24 -.20 + .24 These are the only c o r r e l a t i o n s where .20 < r_ < -.20 out of 576 c o r r e l a t i o n s . 55 tests scores < .20 < r < -.20) . It i s not altogether surprising that the CPT raw scores show l i t t l e r elationship to either colour v i s i o n or a b i l i t y variables. I t i s , however, very surprising that the CPT scores show only low and infrequent co r r e l a t i o n s with the 16PF personality scales. One would assume, and Schaie and Heiss (1964) have stated, that, i f the CPT raw scores, syndrome scores, or sequence formulae scores are to be v a l i d predictors of personality c h a r a c t e r i s t i c s , then the correlations between s p e c i f i c raw scores and c e r t a i n personality scales should be highly s i g n i f i c a n t . As can be seen from Table 6, t h i s assumption i s d e f i n i t e l y not j u s t i f i e d . A l l of the co r r e l a t i o n s are very low, with only 3 out of 576 having any magnitude at a l l , and none being s i g n i f i c a n t ( j> >. 5). , Because of these discouraging findings using the CPT raw scores, the correlations between the CPT weighted colour scores (Appendix II) and the other variables were calculated. lf Table 7 shows these correlations and, as can be seen quite readily, these results are even more disheartening than the above findings. , I f the CPT i s to have any v a l i d i t y , the weighted colour scores (which are based on C a t t e l l * s 42 bipolar personality t r a i t s ) should be s i g n i f i c a n t l y correlated with C a t t e l l * s 16PF personality dimensions. Obviously t h i s i s not the case. Out of a t o t a l of 672 corr e l a t i o n s , only 6 are of any mentionable magnitude and these are too weak to j u s t i f y speculation about underlyinq connections. The age discrepancy Table 7 Interbattery Correlations Between Colour Pyramid Test (CPT) Weighted Colour Scores and Other Variables (a) CPT Weighted Colour Scores and Colour V i s i o n Scores CPT Weighted Colour Scores Colour V i s i o n Correlations Scale 34 (carefree/anxious) 100-Hue + .25 Scale 41 (expressive/secretive) 100-Hue +. 21 Scale 12 ( i n t e l l i g e n t / s t u p i d ) YBMR -.20 Scale 18 (socia YBMR + .23 Scale 18 (sociable/self-contained) YBMMP + .22 Scale 38 (adult/naive) YBMR -. 20 Scale 38 (adult/naive) YBMMP -.25 Scale 10 (happy/sad) YBMMP + .21 Scale 38 (adult/naive) CAT time •'• .22 Scale 25 (modest/attention-seeking) CAT time -.21 continued . These are the only c o r r e l a t i o n s where .20 < r_ < -.20 out of 588 co r r e l a t i o n s . Table 7 continued (b) CPT Weighted Colour Scores and A b i l i t i e s (CAB) CPT Weighted Colour Scores A b i l i t i e s (CAB) Correlations Scale 34 (carefree/anxious) Ms .20 Scale 21 (conscientious/unscrupulous) Aiming .25 (c) CPT Weighted Colour Scores and Per s o n a l i t y (16PF) CPT Weighted Colour Scores 16PF Correlations Scale 37 (independent/dependent) "A" -.20 Scale 26 (open/defensive) " I " -.25 Scale 33 ( t a l k a t i v e / s i l e n t ) . " I " -.20 Scale 35 ( t a s t e f u l / i n a r t i s t i c ) " I " -.20 Scale 20 (obedient/disobedient) "L" -.20 Scale 34 (carefree/anxious) "M" .25 These are the only c o r r e l a t i o n s where .20 < r_ < -.20 out of 378 c o r r e l a t i o n s . These are the only c o r r e l a t i o n s where .20 < x_ < -.20 out of 672 c o r r e l a t i o n s . 58 (Schaie and Heiss tested 15 to 18 year old males while the present sample was 18 to 30 years old) weakens the comparison but does not j u s t i f y disregarding i t . I f s i g n i f i c a n t relationships do e x i s t between the CPT and the 16PF personality factors f o r a teenage population, then the stronger of these relationships should, one would hope, carry over to s l i g h t l y older samples. Because of the general, o v e r a l l poor performance of the CPT i n predicting personality c h a r a c t e r i s t i c s , i t was not included i n the f i n a l three major analyses. The reader should be cautioned at t h i s point against too strong a conclusion about these r e s u l t s as the population i n Schaie and Heiss«s study consisted of teen-age males and t h e i r t o t a l sample size was only 100 which may affect the r e l i a b l i t y of the findings. B. INTERNAL FACTOR ANALYSIS OF COLOUR VISION VARIABLES An i n t e r n a l factor analysis of the 13 colour vision variables was undertaken to determine the degree of communality between any of the colour vision t e s t s ; to determine whether there are any underlying l i n k s between the tests or i f each test i s a measure of a separate, s p e c i f i c dimension of colour visi o n . The Alberta General Factor Analysis Program { AGFAP ) (Hakstian and Bay, 1973) was used i n t h i s analysis. AGFAP i s a "comprehensive ... integrated program ... that permits the user to perform v i r t u a l l y any facet of a factor 59 analysis using currently preferred procedures" (Hakstian and Bay, 1973). The f i r s t step i n AGFAP i s the computation of Pearson product-moment co r r e l a t i o n c o e f f i c i e n t s between a l l of the input variables. The next step involves the factoring of t h i s matrix according to either component or common-factor models. From t h i s , oblique or orthogonal factor transformations are performed, factor score c o e f f i c i e n t matrices are compiled and the actual factor scores are calculated. The f i r s t analysis performed using AGF&P was the computation of an unrotated factor pattern matrix according to the p r i n c i p a l component model. This procedure i s used to determine the l i m i t s to the number of factors which w i l l be derived, the minimum number of independent dimensions needed to account for most of the variance i n the o r i g i n a l set of variables. This i s done by studying the eigenvalues of the 13 x 13 matrix for the colour vision variables to determine the optimal number of factors that can be extracted from the data. Unfortunately, "a unique solution i s ... not t h e o r e t i c a l l y possible, i n that the decision reached regarding the *true* dimensionality of a domain of variables depends e n t i r e l y upon which one of a number of seemingly reasonable operationalizations of the 'correct* number of f a c t o r s i s employed" (Hakstian and fluller, 1973, p., 461). Three methods were used to solve t h i s problem: the Kaiser-Guttman Bule, the Scree t e s t , and the Likelihood-Batio t e s t . 60 The Kaiser-Guttman Rule (Kaiser, 1960) suggests that the number of factors be equal to the number of eigenvalues which exceed unity. This method would lead to a four factor solution for the present data but a perfunctory examination of the data shows four factors to be too many. C a t t e l l (1966) arrived at the widely-used "scree" test which tests for the "break in the curve" of plotted latent roots. This procedure suggests a two factor solution. The Likelihood-Ratio test (Joreskog, 1967) i s associated with the maximum like l i h o o d method of fa c t o r analysis and suggests a three factor solution for the present data. Since both the two- and three-factor solutions appear reasonable from the data, i t was decided that both solutions would be calculated i n order to furnish a better understanding of the problem. Maximum l i k e l i h o o d factor analysis solutions were obtained which were then rotated according to the Harris-Kaiser (1964) l o g i c , f or both the two- and three-factor solutions, the Harris-Kaiser oblique transformations being performed, covering the f u l l range of alt e r n a t i v e s regarding o b l i q u i t y of the factors (see Hakstian, 1974). In both cases, the Case II " &*A~ proportional to L " {Harris and Kaiser, 1964) solutions were best, and are reported i n t h i s study. The resultant oblique primary-factor pattern matrices are shown i n Table 8. In t h i s Table, the underlined values (greater than ± .30) designate the variables which have s i g n i f i c a n t loadings on each factor. The communality, a 2 , i s the sum of Table 8 Oblique Primary-Factor Pattern Matrices for Internal Analysis of Colour V i s i o n Tests Two-Factor Solution Three-Factor Solution Variables I II h 2 I II III h 2 CAT Blue -.07 CAT Red .14 CAT Green .01 CAT Yellow .06 CAT Time .07 BCMT .05 100-Hue .23 RGMR .36 RGMMP -.03 YBMR . 97 YBMMP _^ _78 GBMR ^74 GBMMP .59 Factor Variances 2.74 .40 .16 .06 .34 .15 .06 .39 .15 .02 •31 .11 .13 .16 .03 -.04 .44 .21 -.04 •54 .38 -.06 .43 .36 -.03 •25 .06 .02 .01 .95 ^J39 -.09 .59 ^ .20 .64 .03 .08 .37 .08 1.41 4.15 1.27 -.17 .51 .24 .09 ^34 .15 -.02 .18 -.03 ^ 3 .13 .07 .18 .04 .12 ^38. - 1 8 .26 ^50 .37 .42 .36 .36 -.08 .28 .07 .64 .03 .81 .10 .01 .99 .86 .07 .81 .64 -0.4 .45 2.13 1.39 4.79 continued Table 8 continued Correlations Among Primary Factors II II III I II 1.00 .16 1.00 I II III 1.00 .50 . .09 1.00 .24 1.00 63 squares of the loadings {the sum of a l l of the common factor variance of a test) and i s given in the l a s t column f o r each of the solutions. The bottom of Table 8 presents the int e r c o r r e l a t i o n s among the primary factors for each solution. Investigation of Table 8 reveals that, f o r the two-factor solution, factor I includes a l l anomaloscope variables (with the exception of EGHUP) while factor II includes a l l non-anomaloscope te s t s {excluding CAT time) plus BGMB. The anomaloscope RGMB i s the only variable with f a c t o r i a l complexity, loading almost equally on both factors. For the three-factor solution, variables that had loaded on factor II i n the two-factor solution are now a l l loading on factor I I I but the former fa c t o r I has now s p l i t into two seperate factors. Factor I now contains only the yellow-blue anomaloscope variables { YBHB, YBMMP ) while factor II has BGMB, YBHB, G8MB, AHD GBMHP. F a c t o r i a l complexity i s introduced by YBMS which loads on both factors I and II (but more heavily on II) and by RGMR which loads almost equally on factors II and I I I . This s p l i t t i n q of the two-factor Factor I int o the threes-factor Factors I and II i s evidenced by the corr e l a t i o n s between the factors. The low co r r e l a t i o n (r=.16) between the facto r s i n the two-factor solution i s repeated in the three-factor solution by the low cor r e l a t i o n s between I and I I I (r=.09) and II and III (r—.24) but the closer linkaqe between the three-factor Factors I and II i s evidenced by the hiqher c o r r e l a t i o n (r=.50). 64 C. INTERBATTERY FACTOR ANALYSIS: COLOUR VISION AND ABILITIES In order to establish factors which can be hypothesized to account for the cross-battery relationships, the Tucker (1958) procedure for interbattery factor analysis was performed on the 13 colour v i s i o n and nine a b i l i t y variables. Using t h i s technique, f a c t o r s are determined from the c o r r e l a t i o n of the tests in one battery with the tests in the other battery, thus yielding factors which are common to the two b a t t e r i e s and not those only represented in one of the two b a t t e r i e s . A large-sample chi-sguare test of s i g n i f i c a n c e to determine the minimum number of factors j u s t i f i e d by the data was applied and indicated that there was only one underlying factor. The interbattery factor loadings for each battery are presented i n Table 9 with the s i g n i f i c a n t loading { > .29) underlined. These r e s u l t s indicate the strongest l i n k s are exerted by BCJ3T, 100-Hue, s p a t i a l , associative memory and aiming with lesser, but s t i l l s i g n i f i c a n t , contributions coming from CAT Red, CAT Yellow, REMR, YBHR, GBMR, numericaal and span memory. D. INTERBATTERY FACTOR ANALYSIS: COLOUR VISION AND PERSONALITY Tucker's (1958) procedure for interbattery factor analysis {as discussed above) was applied to the 13 colour v i s i o n and 16 personality variables. The large-sample chi-sguare test of s i g n i f i c a n c e for the minimum number of factors indicated that two factors were present. In order for the factors to be 65 Table 9 Interbattery Factor Pattern for Colour V i s i o n and A b i l i t y B a t t e r i e s Battery 1 Battery 2 Colour V i s i o n CAB A b i l i t i e s Variable Loading Variable Loading CAT Blue CAT Red CAT Green CAT Yellow CAT Time BCMT 100-Hue RGMR RGMMP YBMR YBMMP GBMR GBMMP ,175 331 ,098 299 ,099 527  ,581  343 019 .335 ,178 ,366 , 100 Verbal (V), .251 Numerical (N) .306 Sp a t i a l (S) .550 Speed of Closure (Cs) .269 Perceptual Speed (P) .179 F l e x i b i l i t y of Closure (Cf) .214 Associa t i v e Memory (Ma) .567 Span Memory (Ms) .342 Aiming (A) .471 66 interpretable, transformation of the interbattery f a c t o r s to the simple structure position was es s e n t i a l . For t h i s purpose, Hakstian»s (1976) technigue for two matrix orthogonal rotations was employed because, " unless the same transformation i s applied to 1' (the i n i t i a l factor patterns for the two batteries) , "the maximal interbattery r e l i a b i l i t i e s (defined loosely as the extent to which the interbattery factor scores for the two batteries agree when estimated separately from observed variables i n the two batteries) achieved i n the i n i t i a l f a ctoring are diminished" (Hakstian, 1976, p.269). The resultant interbattery primary factor pattern matrix i s presented i n Table 10. The portion of the factor pattern matrix i n Table 10 above the broken l i n e represents the structure of the colour vision variables necessary to account for the inter-domain relationships, and the portion below the broken l i n e represents the structure, on corresponding interbattery factors, of the personality t r a i t s necessary to account for the inter-domain rel a t i o n s h i p s . The interbattery factor c o r r e l a t i o n s , shown at the bottom of the Table, indicate factor s t a b i l i t y from battery 1 to battery 2, any s i g n i f i c a n t loadings ('"2: .29) being underlined. Table 10 reveals that interbattery Factor I has s i g n i f i c a n t loadings from four colour vision variables (CAT Blue, CAT Bed, BCHT, 100-Hue) and three personality variables (A, Q2, Q4) while Factor II has loadings from three colour v i s i o n variables (YBHB, 67 GBHB, GBHSP ) and foar personality t r a i t s (B, E, fl, H). . Table 10 Interbattery Primary Factor Pattern of Matrix: Colour V i s i o n and Personality Variable Interbattery Factors I II Colour V i s i o n : CAT Blue .373 -.182 CAT Red .477 .190 CAT Green .136 .228 CAT Yellow .086 -.095 CAT Time .177 -.099 BCMT .384 -.141 100-Hue .392 -.046 RGMR .010 .202 RGMMP .127 -.149 YBMR .090 .423 YBMMP .107 .206 GBMR .046 .469 GBMMP .065 .309 16 PF: A (Sizothymia vs Affectothymia) -.290 .088 B ( C r y s t a l l i z e d I n t e l l i g e n c e ) .278 .389 C (Ego Strength) .204 .160 E (Submissiveness vs Dominance) -.220 .292 F (Desurgency vs Surgency) -.123 .217 G (Superego Strength) .089 -.003 H (Threctia vs Parmia) -.197 • 353 I (Harria vs Premsia) -.058 .059 L (Alaxia vs Protension) -.029 .108 M (Praxernia vs Autia) .240 .267 N (Naivete vs Shrewdness) .113 -.445 0 (Guilt Proneness) -.073 -.102 Ql (Conservative vs Experimenting) .089 .060 Q2 (Self S u f f i c i e n c y ) .436 .083 Q 3 (Self Sentiment Strength) .285 .009 Q4 (Ergic Tension) -.305 .056 continued Table 10 continued Interbattery Factor Correlations I II I 1.000 II -.194 1.000 70 PISCOSSION A. INTERNAL ANALYSIS OF COLOUR VISION TESTS I: Two-Factor Solution The primary factor pattern matrix for the i n t e r n a l factor analysis of the 13 colour vision t e s t s (see Table 8) indicates that, for the two factor solution, the factors s p l i t between * anomaloscope» and »non-anomaloscope* categories. The underlying l i n k i n the s p l i t between the two factors seems to be either (1) surface colours versus l i g h t s , or (2) self-administration versus experimenter manipulation. The f i r s t p o s s i b i l i t y suggests that the difference between the two factors i s due to the d i f f e r e n t i a l e f f e c t of test surfaces: Factor I encompasses the anomaloscope axes — those using transmitted l i g h t s as test s t i m u l i ; Factor II involves the CAT (except time), BCHT, and 100-Hue variables — those using r e f l e c t i n g coloured surfaces as test s t i m u l i . Factor complexity i s r e f l e c t e d i n the almost equal loading of the RGMR on both factors. Unexplored variables a f f e c t i n g the surface colours (e.g., fading and s h i f t i n g of the colours as they age) combined with the effects of continuous handling of these surfaces by subjects could r e s u l t i n a systematic bias i n performance when 71 using these s t i m u l i when compared to performances using non-fading, non-handled anomaloscope f i l t e r s . The second p o s s i b i l i t y suggests that the difference i s due to the d i f f e r e n t i a l e f f e c t s of test administration: s e l f -administration versus expermenter manipulation. In the anomaloscope (Factor I v a r i a b l e s ) , the experimenter adjusts the s t i m u l i i n response to the subject's judgement of the sameness or difference of the two l i g h t e d sides, the object being for the experimenter to establish the widest range of colour combinations the subject w i l l acept as being i d e n t i c a l to the standard side. Once a matching range i s established for each of the three sets of s t i m u l i , i t i s checked using the same procedure. Conversely, i n the *non-anomaloscope* variables (Factor I I ) , the experimenter presents the entire t e s t to the subject and the subject manipulates each t e s t unit, changing and adjusting his decision u n t i l he i s s a t i s f i e d with h i s performance. The experimenter does not i n t e r a c t with the subject during t h i s decision process and such extraneous variables as fatigue, boredom, or imperfections i n the surfaces (due to aging or handling as mentioned above) may a l l play a part in the diligence and accuracy with which the subject performs the task. In the anomaloscope tests, on the other hand, the experimenter i s constantly i n t e r a c t i n g with the subject, questioning and prodding f o r responses. This s i t u a t i o n could e a s i l y be construed by the subject as more competitive and demanding, thus reguiring 72 more attention and constant alertness to the task. Moreover, since the same experimenter supervised a l l tests except the anomaloscope, further increased attentiveness may have resulted from the novelty of a new experimenter f o r t h i s t e s t . Thus, increased motivation combined with the r e l a t i v e lack of surface imperfections i n Factor I variables may lead to the difference i n responses between the two types of t e s t s and therefore the clear delineation of each as a separate factor. In t h i s analysis, no supporting data was c o l l e c t e d to add more or less weight to e i t h e r the surface-versus-light or the self-versus-experimenter manupilation hypothesis. The f a c t that a l l surface colour tests are very well standardized and that precautions were taken to minimize surface imperfections weakens, but does not destroy, the c r e d i b i l i t y of the surface-versus-light approach. This, plus the fact that fatigue and boredom l i k e l y played a part in a subject's performance (each subject spent 125 minutes doing the surface colour t e s t s ) , leads the author to support the second, self-versus-experimenter manipulation hypothesis. Moreover, i t seems reasonable that the experimenter-subject interaction and forced-choice decisions involved in the anomaloscope testing would have some e f f e c t on the accuracy of the subject's responses. I I : Three-Factor Solution The three factor solution for the i n t e r n a l factor analysis 73 of the 13 colour v i s i o n variables i s a further refinement of the two-factor solution; the non-anomaloscope variables (except CAT time) constitute Factor III while the anomaloscope variables s p l i t between Factors I and II (see Table 8). The rati o n a l e for the Factors I and II versus Factor III follows the hypotheses set out i n the previous section, however the rationale underlying the d i v i s i o n between the f i r s t and second factors i s somewhat more elusive. The three-factor solution in Table 8 shows that Factor I consists of YBMR and YB8MP while Factor II consists of RGBS, YBMR, GBHR and G8MHP, f a c t o r i a l complexity being introduced by YBMR which loads more heavily on Factor II than Factor I (loading .39 and .64 respectively). I n i t i a l l y , the author investigated the hypothesis that the I-II d i v i s i o n was due to an age factor since the YB eguation i s most read i l y affected by aging (Lakowski, 1964). However, an examination of the correlations between age and the anomaloscope variables (see Appendix III) seems to discount t h i s hypothesis; a l l correlations with age are non-significant { .10 > r > -.10 except the corr e l a t i o n with RGMR where r=-. 19) . That the anomaloscope data are not affected by an age variable i s readily understandable as the sample tested was r e l a t i v e l y homogeneous with respect to age (range was 17 to 30 years) and i t i s known that the effects of aging usually become more noticeable at l a t e r stages i n l i f e (Ohta and Kato, 1976; Lakowski, 1964; 1969; 74 1970a; 1972). A more plausible hypothesis to explain the d i v i s i o n between Factors I and II concerns the degree of the subject's myopia or near-sightedness. Ho data regarding myopia i n subjects was gathered i n t h i s experiment, but i t has been hypothesized that myopia w i l l show a more severe ef f e c t on the yellow-blue anomaloscope equation than on either the red-green or green-blue equations (Lakowski and Oliver, 1972). Although the exact cause i s not yet f u l l y understood, Lakowski (in a personal communication) has stated that other of h i s studies have noted the uniqueness of the yellow-blue equation i n his c l i n i c a l populations. This could mean that the yellow-blue equation i s actually d i s t i n c t from the others i n the aspect of colour vision that i t i s measuring, a hypothesis which i s supported by the present findings. Further experiments are necessary i n t h i s area before t h i s hypothesis can be more d e f i n i t i v e l y accepted or rejected. B. INTEBBATTEBY FACTOR ANALYSIS: ABILITIES AND COLO0B VISION The r e s u l t s for the interbattery factor analysis of the 13 colour v i s i o n and nine a b i l i t i e s variables are presented i n Table 9. Since there i s only one interbattery f a c t o r , these r e s u l t s are very d i f f i c u l t to interpret, given the present l e v e l of information, but some observations can be made. The dominant c h a r a c t e r i s t i c of the factor appears to be the 75 element of memory —• the Colour Memory Test and the 100-Hue (involving short-term memory) and Spat i a l , associative Memory, Span Memory, and Aiming carry the most weight. Since a l l loadings are posi t i v e , i t would appear that a person who performs well on the colour memory tests w i l l usually perform well on the a b i l i t i e s memory tes t s . I n t u i t i v e l y , i t would seem that, for example, on the test of s p a t i a l perception (S), a person with a good v i s u a l memory w i l l r etain the stimulus figure i n memory for a longer time, wasting l e s s time r e f e r r i n g back to i t , and therefore receiving a higher score. S i m i l a r l y on the colour vi s i o n tests ( i . e . , BCMT), a person with a superior v i s u a l memory w i l l r etain a more exact representation of the test colour and thus be more accurate i n his choice of the matching colour. In order to test t h i s hypothesis, further experimentation i s necessary to investigate these aspects of memory more completely., C. INTERBATTERY FACTOR ANALYSIS: PERSONALITY AND COLOUR VISION The interbattery primary factor pattern matrix between the 13 colour vi s i o n variables and the 16 personality variables (see Table 10) indicates that there are two underlying factors crossing these two domains. Factor I indicates that persons performing better on the CAT Blue and Red scales, who have better colour memory (BCMT) 76 and better surface colour discrimination (100-Hue) were generally more reserved and detached ( A - ) , more s e l f - s u f f i c i e n t (Q2+), and more relaxed and tr a n g u i l (Q4 -). , This personality p r o f i l e might describe an introverted i n d i v i d u a l who has confidence i n himself, perhaps a "bookwormish" academic type. However, one can only speculate on the relationship between these personality c h a r a c t e r i s t i c s and the colour vision variables, w.hy t h i s personality type should perform better on the CAT Blue and Red scales i s unclear, but the higher scores on both the BCMT and the 100-Hue could r e f l e c t t h i s higher s e l f -confidence {i.e., the higher confidence may lead to the making of rapid decisions which i s a major asset in the colour memory test since the memory of the test hue rapidly becomes distorted with time). These two test scores may also r e f l e c t the ch a r a c t e r i s t i c of s e l f - s u f f i c i e n c y — the subject, as a result of his superior a b i l i t y to use inner resources, may perform better on self-administered tests than a subject who i s less s e l f - s u f f i c i e n t . (See the discussion of the colour vi s i o n factors for a more complete coverage of the self-administered versus experimenter-manipulated aspects of the tests.) Factor I I also suggests the studious character but tends to stress the competitive, f o r t h r i g h t i n t e l l i g e n c e as opposed to the reserved, t r a n g u i l "bookworm". This factor suggests that a person who performs well on the anomaloscope YBMR, GBMR, and GBMMP w i l l also have higher c r y s t a l l i z e d i n t e l l i g e n c e (B+), be 77 more assertive, stubborn and competitive (E+), be more adventurous and s o c i a l l y bold (H+), and be more f o r t h r i g h t and unpretentious (N -). Again, although these personality c h a r a c t e r i s t i c s hang together very n i c e l y i n themselves, t h e i r r e l a t i o n s h i p with the colour vi s i o n variables can only be speculative at t h i s point. This assertive, i n t e l l i g e n t person has better discrimination on the Yellow-Blue and Green-Blue axes as measured by the anomaloscope but the l i n k with these personality c h a r a c t e r i s t i c s can only be c l a r i f i e d through further, more detailed experimentation i n which s p e c i f i c colour v i s i o n and personality t r a i t s are investigated i n much greater depth and d e t a i l . Nonetheless, i t i s i n t r i g u i n g to consider possible explanations for these variables loading on the same factor. For example, one possible connection could be that the experimenter-manipulated aspect of the anomaloscope te s t s (as mentioned above) could bring out competitive t r a i t s i n a subject. It i s possible that t h i s type of subject performs better in si t u a t i o n s where there i s an "appreciative audience" as opposed to situations where he must motivate himself throughout the entire test with no in t e r a c t i o n with another person.. Therefore, although no d e f i n i t e conclusions can be drawn about the differences between the two f a c t o r s given the present l e v e l of information, i t would appear that the s p l i t i s between a reserved, relaxed "bookworm" who performs best on s e l f -78 manipulated surface colour tests, and an aggressive, fo r t h r i g h t academic who excels on the experimenter-controlled l i g h t t e s t s . These findings d e f i n i t e l y indicate that further experimentation i s e s s e n t i a l so that t h i s unknown area can be c l a r i f i e d and our present understanding of these relationships made more complete. D. COMPARISON OF PRESENT FINDINGS WITH LAKOWSKI (1970b) Regarding the r e l a t i o n s h i p between colour v i s i o n and a b i l i t y variables, Lakowski (1970b) found that the "relationships between scores on the cognitive tests and those for the 100-Hue and the BCMT have been found, most of them at the 0.01 s i g n i f i c a n c e l e v e l . However i n none of these cases are the c o r r e l a t i o n s much higher than about 0.3 or 0.4" (p. 82). On the other hand, Lakowski found no association between cognitive test performance and the CAT items (except CAT total) or the anomaloscope matching ranges or mid-matching points. These findings are not supported by the present r e s u l t s which revealed only four s i g n i f i c a n t c o r r e l a t i o n s between the colour vision and the a b i l i t y variables: 100-Hue with Numerical (r=+0.32) BCMT with Associative Memory (r=+0.42) CAT Red with Spatial (r=+0.32) GBMR with Aiming (r=+0.34) 79 these were the only s i g n i f i c a n t relationships oat of 117 correlations which indicates that, for an older age group, the connections with the 100-Hue and BCMT which Lakowski found become weaker and les s clear-cut. Lakowski also found no s i g n i f i c a n t c o r r e l a t i o n s between personality c h a r a c t e r i s t i c s and the 100-Hue or BCMT variables but found 17 s i g n i f i c a n t relationships between CAT and anomaloscope variables and personality factors (see Table 11), but the present study showed only one noteworthy c o r r e l a t i o n between CAT Bed and fact o r Q4 (Ergic Tension) . I t would again appear that the introduction of the age factor has helped to reduce, or eliminate, the connections between the colour vision and personality variables which Lakowski found with his younger population. I t i s in t e r e s t i n g to note the d i f f e r e n t grouping of colour vi s i o n tests that emerged from each study. In h i s findings, Lakowski constantly distinguished between the 100-Hue and BCMT as opposed to the CAT and the anomaloscope., The present study places a l l surface colour, self-manipulated test (100-Hue, BC8T, CAT) together as opposed to the l i g h t , experimenter controlled anomaloscope tests. Although no explanation can be posited at t h i s time with the present l e v e l of understanding, t h i s area obviously requires further experimentation i n order --that t h i s discrepancy be resolved. Table 11 Int e r c o r r e l a t i o n s Among Personality and Colour V i s i o n Variables (as per Lakowski, 1970b) 80 C o l o u r V i s i o n V a r i a b l e s P e r s o n a l i t y V a r i a b l e s Sign of Corre l a t i o n CAT Red CAT Yellow C (Ego S t r e n g t h ) n e g a t i v e G (Superego S t r e n g t h ) I (Tough-minded) 0 ( A p p r e h e n s i v e ) n e g a t i v e N e u r o t i c i s m YBMMP RGMR YBMR H (Restraint) J (Self-Doubt) Introversion Anxiety Q3 (Controlled) Extraversion Neuroticism G (Conscientious) H (Venturesome) Q 3 (Controlled) Extraversion Anxiety p o s i t i v e p o s i t i v e p o s i t i v e 81 SUHMARY AND CONCLUDING REHARKS The present in v e s t i g a t i o n , an extension and modification of a study by Lakowski (1970b).,. was designed to investigate possible underlying r e l a t i o n s h i p s between colour v i s i o n , a b i l i t y and personality dimensions. Thirteen colour vision, nine a b i l i t y and sixteen personality variables were included i n the f i n a l analysis which had three sections: (1) i n t e r n a l factor analysis of the colour v i s i o n variables, (2) interbattery factor analysis of colour vision and a b i l i t y variables, and (3) interbattery factor analysis of colour v i s i o n and personality variables. The two-factor and three-factor solutions to the i n t e r n a l colour v i s i o n analysis were discussed.- In the two-factor solution, the underlying difference between the two factors appears to be surface colours versus l i g h t s or s e l f manipulation versus experimenter administration or possibly some combination of each. The three-factor solution retains t h i s s p l i t but the one anomaloscope, l i g h t or experimenter administered factor now s p l i t s i n t o two separate factors, one being a yellow-blue equation factor and the other factor consisting of the red-green and green-blue equations., Although supportive data was not available, i t i s possible that t h i s s p l i t i s due to the subject's myopia which has a more marked e f f e c t on the yellow-82 blue equation than on either the red-green or green-blue eguations. Another p o s s i b i l i t y which seems more l i k e l y from Lakowski»s findings, i s that the yellow-blue equation i s unique i n the aspect of colour v i s i o n that i t i s testing while the red-green and green-blue eguations are more s i m i l a r to each other. Further studies i n t h i s area are obviously necessary before one can accept or rej e c t these hypotheses. The interbattery factor analysis of the a b i l i t i e s and colour vision dimensions yielded only one factor. Although s u f f i c i e n t supporting data was not av a i l a b l e , i t appears that the underlying connection i s a memory factor, meaning that a person with a better memory w i l l perform better on both a b i l i t y and colour vision tests. ., The personality and colour v i s i o n interbattery factor analysis yielded two primary interbattery factors. The f i r s t factor was a "bookwormish", reserved and relaxed i n d i v i d u a l who does well on the CAT Red and Blue scales, the BCMT and the 100-Hue while the second factor describes the competitive, aggressive i n t e l l e c t u a l who does better on the anomaloscope YBMR, GBHR, and GBSMP. It i s l i k e l y that t h i s difference between the factors i s due to the more s e l f - r e l i a n c e , self-manipulated aspects of the surface colour tests (Factor I) as opposed to the more competitive, experimenter-controlled aspects of the anomaloscope tests (Factor I I ) . Comparison of the present findings with those of Lakowski 83 (1970b) show l i t t l e s i m i l a r i t i e s . Ehereas Lakowski found that h i s cognitive variables correlated highly with the 100-Hue and BCHT and not at a l l with the CAT or anomaloscope variables, the present study found one s i g n i f i c a n t c o r r e l a t i o n between the a b i l i t i e s and each of the 100-Hue, BCHT, CAT and anomaloscope tests. In the personality-colour vision investigation, Lakowski found no l i n k s between personality t r a i t s and either the 100-Hue or BCMT variables but found many s i g n i f i c a n t correlations between personality variables and CAT and anomaloscope variables. The present study, on the other hand, showed only one s i g n i f i c a n t c o r r e l a t i o n between the 16PF's ergic tension (Q4) and CAT Red. Although a closer comparison of Lakowski's data with the present findings i s necessary to understand these differences more f u l l y , i t i s l i k e l y that the discrepancy i s due to the age difference i n thatLakowski's population was young teenagers while the present sample was adult. Generally, the present study has found that (1) there i s a clean d i s t i n c t i o n between two types of colour v i s i o n t e s t s ; (2) there i s an underlying connection between colour v i s i o n and mental a b i l i t i e s (as measured by the tests used); (3) there i s a deeper connection between colour vision performance and personality t r a i t s . , A note of caution should be interjected at t h i s point about drawing too strong conclusions about colonr v i s i o n mechanisms 84 based upon the present findings. These findings may be due to method variance which i s s p e c i f i c to the colour v i s i o n tests used; the results may be an a r t i f a c t s p e c i f i c to the tests. Ideally, i f one could f i n d s a t i s f a c t o r y t e s t s , one would administer self-manipulated l i g h t tests and experimenter-controlled surface colour tests to the subjects so that t h i s s p e c i f i c method variance could be reduced, thus allowing the r e s u l t s to be more generalizable to o v e r a l l colour vision mechanisms rather than s p e c i f i c to the t e s t used i n the study. This i n i t i a l study has c l e a r l y demonstrated that l i n k s exist between colour v i s i o n , a b i l i t y and personality c h a r a c t e r i s t i c s , i n d i c a t i n g that some causal connection could be involved which allows a person with higher l e v e l s of some a b i l i t y or personality attributes to perform better on s p e c i f i c colour v i s i o n tasks. Although colour vi s i o n tests were i d e a l l y designed to measure only colour v i s i o n , devoid of extraneous interference, these findings show that, at present, t h i s i s not possible. Given the structure of our present tests which reduces the colour v i s i o n task to i t simplest, most basic form, one s t i l l cannot escape the deeper influence of the i n d i v i d u a l ' s personality or a b i l i t y make-up on the performance of these tasks. Colour vision i s not simply an is o l a t e d information coding process but rather a complex sensory and cognitive network i n which the s p e c i f i c a b i l i t y and personality c h a r a c t e r i s t i c s of the i n d i v i d u a l may i n t e r a c t with the 85 information coding process at various l e v e l s , thus a l t e r i n g i t uniguely f o r that i n d i v i d u a l . Further research i n these areas i s es s e n t i a l i n order that these interactions can be more f u l l y understood and the design of colour vision t e s t s modified so as to eliminate, or account f o r , the e f f e c t s of these c h a r a c t e r i s t i c s . 86 BIBLIOGRAPHY Birren, F. Color preference as a d u e to personality.. Art Psychotherapy, 1973, J , 13-16. Brown, R. , W. and Lenneberg, e. H. A study i n language and cognition^ Journal of - Abnormal and • S^claJL- Psychology, •• 1954, 49, 454-462. Burdick, J. A. The Color Pyramid Test: A c r i t i c a l evaluation. Journal of Psychology, 1968, 70, 93-97. Burnham, R. 8. and Clark, J.r. A colour memory test. JOSA, 1954, 44, 658-659. Burnham, R. W. and Clark, J.R. A test of hue memory. Journal of i E f i l i e d Psychology, 1955. 39, 164-172. Burnham, R. W., Hanes, R. M., and Bartleson. C.J. Color: A Guide to Basic Facts and Concepts. New York: John Wiley and Sons, 1963. C a r r o l l , J. B. The f a c t o r i a l representation of mental a b i l i t i e s and academic achievement. Bducational Psychological IS 2 sure men % J L 1943, 3, 307-322. C a t t e l l , R. B. The Description- and Measurement of Personality. New York: World Press, 1946. C a t t e l l , R. B. Personality and Motivation:. Structure and Measurement. -New York: World Book, 1957. C a t t e l l , R. B. Factor analysis: an introduction to essentials. I: The purpose and underlying models. Biometrics. 1965a, 21 (1) , 190-215. C a t t e l l , R. B. Factor analysis: an introduction to essentials., I I : The ro l e of factor analysis in research. Biometrics^ 1965b, 21<2), 405-435. C a t t e l l , R.B. The Scree test for the number of factors. Multivariate Behavioral Research, 1966, j , 245-276. C a t t e l l , R. 8. A b i l i t i e s : Their Structure, Growth and Action. -t Boston: Houghton-Mifflin Company. 1971. 87 C a t t e l l , B. B. And Beloff, H. Handbook for the Jr.-Sr. High School Personality Questionna i re. C h a m pa i g n , 11lin o i s: I n s t i t u t e for Personality and A b i l i t y Testing (IPAT), 1962. C a t t e l l , B..B., Eber, H. W. And Tatsuoka, H. M. Handbook for the Sixteen Personality Factor Questionnaire. Champaign, I l l i n o i s : IPAT, 1970., C o l l i n s , W. E., Casola, A. S. And Zegers, B. T. The performance of c o l o r - b l i n d subjects on the Color Aptitude Test. Journal of General Psychology. 1961, 64, 245-250. , Cooley, W. H. And Lohnes. P. 1 . a u l t i v a r l a t e Data Analysis. Mew York: John Wiley and Sons, 1971. Dimmick, F. L. A Color Aptitude Test: 1940 Experimental Edition. Journal of Applied Psychology. 1946. 30, 10-22. Dimmick, F. L. S p e c i f i c a t i o n and c a l i b r a t i o n of the 1953 e d i t i o n of the Inter-Society Color Council Color Aptitude Test. Journal of the Optical Society of America (JOSAli. 19 56, 4j6, 389-393. Evans, B. B. The Perception of Color. New York: John Wiley and Sons, 1974. Farnsworth, D. The Farnsworth-Hunsell 100-Hue and dichotomous tes t for color v i s i o n . JOSA, 194 3. 33, 568-578. Farnsworth, D. Manual for the. Farnsworth-Hunsell 100-Hue Te§t fo r the Examination of Color Discrimination. •*/ Baltimore, Haryland: Hunsell Color Company, 1957. Forgus, B. , H. And Helamed, L.: E. • Perception,: ••^•Cog n l M^ve^Staf e-: Approach.,^ (2nn Ed.) New York: McGraw-Hill, 1976. Friedman, B. The r e l a t i o n s h i p between i n t e l l i g e n c e and performance on the Stroop Colour-Work Test i n second- and fifth-grade children. Journal of Genetic Psychology<, 1971, 118, 147-148. French, J . W. The description of aptitude and achievement tests i n terms of rotated f a c t o r s . Psychometric Monographs, No. 5., Chicago: University of Chicago Press, 1951., Fruchter, B. Introduction to Factor A^aly.sis^.-> Toronto: D. van Nosttand Company.,1954. G i l b e r t , J . , G. Age changes i n color matching. Journal of Gerontology^ 1957, 12, 210-215. 88 Hakstian, A. R. The development of a cla s s of oblique factor solutions. B r i t i s h Journal of Mathematics and S t a t i s t i c a l Psicholosjjt. 1974, 27, 100-114., Hakstian* A. R. Two-matrix orthogonal rotation procedures. Esjchometrika^ 1976, 4J[, 267-272. Hakstian, A. R. And Bay, K. S. User's Manual to Accompany the Alberta General Factor Analysis Program fAGFAP) » University of Alberta, D i v i s i o n of Educational Research Services, 1973. Hakstian, A. R. And Muller, V. J. Some notes on the number of factors problem. Multivariate Behavioral Research, 1973, 8, 461-475. Hakstian, A. . R. And C a t t e l l , R. B. The checking of primary a b i l i t y structure on a broader basis of performance.,.- The B r i t i s h Journal of Educationa 1 Psychology;, -1974, 44, 140-154. Hakstian, A. R. And C a t t e l l , R. .. B. Comprehensive A b i l i t y Battery: Preliminary Standardization Manual. 7 Champaign, I l l i n o i s : IPAT, 1975. Hakstian, A. R. And C a t t e l l , R. B. Transformation of axes i n interbattery factor analysis. Multivariate Behavioural Research, •-1977, X2, In press. Harris, C. W. And Kaiser, H. F. Obligue factor analytic solutions by orthogonal; transformations. Psvchornetrika. 1964, 29, 347-362. Hammer, E. F. The B-T-P C1inica1 flesearch Manual* L 7Beverly H i l l s , C a l i f o r n i a : Western Psychological Services, 1955. Hawkins, J . F. The Effect of an Auditory Interference on SJiort-Term Colour Memory. - Unpublished manuscript. University of B r i t i s h Columbia, 1973. Horn* J.>L. Organization of a b i l i t i e s and the development of in t e l l i g e n c e . P sycholofical Review, 1968, 75, 242-259. Jensen, A. R. And Rohwer, «. D. The Stroop Colour-SJord Test: a review. Acta Psychologica. 1966, 25, 36-93. Joreskog, K. G. Some contributions to maximum l i k e l i h o o d factor analysis. Psychometrika. 1967. 32/ 443-482. 89 Kaiser, H. F. The application of electronic computers to factor analysis. Educational and Psychological Measurement, 1960, 20, 141-151., Lakowski, 8.,Age and Colour Vision. Unpublished Ph.D. Thesis i n the Faculty of Social Sciences, Edinburgh University, 1964. Lakowski, S. A c r i t i c a l evaluation of colour vi s i o n tests, g r i t i s h Journal of Physiological Optics, 1966, 23, 186-209. Lakowski, R. Small colour v i s i o n variations and t h e i r e f f e c t i n vis u a l colorimetry. colour Measurement i n industry. Proceedings of a Symposium of Colour Measurement in Industry, 1967a. Lakowski, R. Colour Vision Tests; What- d o T h e y T e s t ? Paper presented to the Scottish Symposium on Colour Vision and Colour Measurement* Edited by R. Lakowski and R. S. S i n c l a i r . Edinburgh, No. 39/1, 1967b. Lakowski, fi. Colour matching a b i l i t y - can i t be measured? 323I5al of the Society of Dyers and Colo u r i s t s . 1968a, J34, 3-9. Lakowski, R. The Farnsworth-Munsell 100-Hue Test. The Ophthalmic Q f i i i c i a n t 1968b, 8, 867~872. Lakowski, R. Theory and practice of colour v i s i o n testing: a review (Parts I and I I ) . B r i t i s h Journal of I n d u s t r i a l Medicine, 1969, 26, 173-189. 265-288. Lakowski, R., Colour Vision Anomalies. Paper presented to the B r i t i s h Association for the Advancement of Science. Durham Meeting, 1970a. Lakowski, R. Psychological variables i n colour v i s i o n testing. In M. Richter (Ed.) Proceedings of the International Colour -Meeting: ^Colour 69". Stockholm: Gottingen Susterschmidt, 1970b, 79-86. Lakowski, R. Ca l i b r a t i o n , validation and population norms f o r the Pickford-Nicolson anomaloscope. B r i t i s h Journal of -Physiological Optics, 1971, 26, 166-182. Lakowski, R. The Pickford-Nicolson anomaloscope as a test f o r acquired dyschromatopsia. Modern Problems i n Ophthalmology.-1972, 11, 25-3 3. 90 Lakowski, R. And Montgomery, G. W. G. Colour Discrimination in Profoundly Deaf Children. Paper presented to the 2nd Scottish Symposium on Colour. Edinburgh University, Edinburgh, 1968. Lakowski, R. And Oliver, K. S t a t i s t i c a l Methods i n Ophthalmology. Paper presented at the Annual Meeting of the Canadian Ophthalmological Society, Harrison Hot Springs, 1972. Lakowski, B. And deBeck, J. Age e f f e c t i n the Burnham-Clark-munsell Color Memory Test. Die Parbe, 1973, 22* 231-238. Lakowski, R. , And Melhuish, P. , W. Objective analysis of the Luscher Colour Test. Die Far.bex 1973, 22, 239-250. Lantz, D. And S t e f f l r e , V. Language and cognition r e v i s i t e d . , j a 3 E B § l 9_f Abnormal and Social Psychology^ 1964, 69, 472-481.; Lantz, D. And Lenneberg, E.,H..Verbal communication and colour memory in the deaf and hearing. Chi 1 d Deve 1 o patentg 1966, 3_7, 765-779. Lawly, D. N. And Maxwell, A. E. Factor Analysis as a S t a t i s t i c a l Method. London: Butterworths, 1971. Lenneberg, E. H. Color naming, color recognition, color discrimination: a re-appraisal. Perceptual and-Motor S k i l l s ^ -1961, 12, 375-382. Lenneberg, E. H. The re l a t i o n s h i p of language to the formation of concepts. Synthese, 1962, J4, 103-109. „ Lenneberg, E. H. B i o l o g i c a l Foundations of Language. New York: John Wiley and Sons, 1967. Lenneberg, E. H. And Roberts, J. M. The Language of Experience. Memoir 13. Indiana University Publication i n Anthropology and L i n g u i s t i c s , 1956. Luscher, M. The Luscher Colour Test._ Translated by I. Scott. New York: Simon and Schuster, 1971. (German o r i g i n a l 1948) . , Odbert, H. A., Karwoski, T. F. And Ekerson, A. B. Studies i n synthetic thinking: I. Musical and verbal associations of color and mood. Journal of General Psychology* 1942, 26, 153-173. ; 91 Ohta, Y. and Kato, H. Colour perception changes with age: test r e s u l t s by P-N anomaloscope. Modern Problems i n QEhthalmoloay^ 1976, V7, 345-352. OVReilley; P. 0., Holzinger, R. And Blewett, D. The P f i s t e r Colored Pyramid Test. Journal of Nervous and Mental Diseases,. 1957, 125, 385-387. O 'Reilley, P. O. And Blewett, D. Color analysis of the Pyramid Test./Piseases of the Nervous System, 1959, 20. 211-213. P f i s t e r , M. Der farbpyramidentest (The Color Pyramid Test). Psychologische Rundsshan. 1950, J , 192-194. Pickford, R. W. A p r a c t i c a l anomaloscope for t e s t i n g colour v i s i o n and colour blindness. B r i t i s h Journal of Physiological Optics. 1957, Jj4, 2-26. Pickford, R. A b r i e f review of some f a c t o r i a l studies of colour v i s i o n . Die Farbe, 1962. Nr. 1/6. 59-68. Pickford, R. Colour. ColQ/ur-^ylglQn^-ajad^ Col oar Blindness. Paper presented to the Scottish Symposium on Colour Vision and Colour Measurement. Edited b y R. Lakowski and a . , S. S i n c l a i r . Edinburgh, No. 39/1.,1967a. Pickford, R. H. Colour blindness: anomaolscope t e s t s and physiological problems. International Jonrna.1 of. Neurology, 1967b, 6(2) , 210-221. Pickford, R. W. And Lakowski, R. The Pickford-Nicolson anomaloscope.,British Journal of Physiological Optics^ 1960, 17, 131-150. Pierce, H. O* D. In dividual Differences i n Normal Colour Vision. Great B r i t a i n Medical Research Council* Special Report No. 181, 1933. Pierce, ft. 0*D. The Selection of Colour workers. London: Pitman and Sons, 1934. Haven, J. C. And Halshaw, j . B. Vocabulary Tests. B r i t i s h Journal of Medical Psychology. 1944, 20, 185-194. Raven, J. C. Guide to Osina the M i l l - H i j l Vocabulary Scale aitfe the Progress!ye Matrices Scale. London: Lewis and Company, 1958. 92 Riffenburgh, G. H. Responses to colour combinations as indices of personality t r a i t s . Journal of General Psycholoqy,1959, 61, 317-322. Rorschach, H. Psychodiagnostics: A Diagnostic Test Based on Perception. New York: Grune and Stratton, 1942. Spearman, C. B. The a b i l i t i e s of Han. New York: Hacmillan, 1927. Schaie, K., H., Scaling the association between colors and mood tones. American Journal of Psychology, 1961a, 74, 266-273. Schaie, K. W. A Q-sort of colour-mood association. Journal of £E2iesMve Jgcjinigjiesa.r 1961b, 25, 341-345. Schaie, K. W. The Colour Pyramid Test: a non-verbal technique for personality assessment. Psyche B u l l ^ 1963, 60, 530-547. Schaie, K.,W. On the r e l a t i o n of color and personality. Journal of Projective Techniques for Personality•-Assessment, 1966, 30, 512-524. Schaie, K. W. And Heiss, R. Colour and Personality: A Manualfor the Colour Pyramid. ;Berne, Switzerland: Hans Huber, 1964. Stroop, J . R. Studies of interference in s e r i a l verbal reactions. Psychological Monographs,1935, No. 5. 93 Thomas, G. , J. Visual s e n s i t i v i t y to color: a comparative study of four tests. American Journal of Psychology. 1943, 56, 583-591. Thurstone, L. L. Primary mental a b i l i t i e s . Psychometric Monographs, 1938, No. 1. Thurstone, L. L. Multiple-Factor Analysis. Chicago: University of Chicago Press, 1947. Thurstone, L. L. And Thurstone, T. G. F a c t o r i a l studies of in t e l l i g e n c e . Psychometric Monogra phs* 1941. No. 2. Tucker, L. S. An interbattery method of f a c t o r analysis. Psychometrika, 1958, 23, 111-135... Vernon, P. E. And Parry, J . B. Personnel Selection i n the B r i t i s h Forces. London: University of London Press, 1949. Wexner, L. B. The degree to nhich colors (hues) are associated with; mood-tones. Journal of Applied Psychology, 1954. 38, 432-435. Hoods, B. A. The Cglgr Aptitude Tegt. I n d u s t r i a l Psychological Laboratories, Color D i v i s i o n . 1952. Woods, W. , A. „<" Some determinants of attitudes toward colors in combination. Perceptual and Motor S k i l l s , 1956. 6, 187-193. APPENDIX I SCOBIHG OF THE COL008 PY8&MID TEST 95 Color Scoring aft e r the test administration has been completed, the scoring procedure begins with an evaluation of the frequencies of color choice and other derived scores. The accompanying figure i l l u s t r a t e s a f u l l y scored record blank. The reader may wich to refer to t h i s f i g u r e throughout the following step-by-step scoring in s t r u c t i o n s . a. Scoring the choices for each of the 24 hues examine the f i r s t pretty pyramid (Ip) and enter the number of choices for each hue i n the appropriate l i n e of column I of the ruled frequency table f o r the pretty pyramids. Add a l l entries i n t h i s column to check that a t o t a l of f i f t e e n choices have been recorded. Repeat the above operaion for pyramids II and IIIp, entering frequencies i n columns II and III repectively. Add the entries i n each l i n e and enter t o t a l s i n column T. These are the frequencies with which each hue has been chosen. B. Scoring the choices f o r each of the color groups add the entries f o r each color in columns I, I I , and III to get the sub-totals for each color for each pyramid {e.g. the sum of the entries i n column I from l i n e s 11, 12, 13, and 14 form the sub-total for Red i n pyramid I ) . Next add the e n t r i e s f o r each color i n the sub-total l i n e s and enter color t o t a l s i n the offset c e l l s i n column T. These c e l l s contain the frequencies 96 with which each color has been chosen. Add the e n t r i e s in a l l the o f f s e t t o t a l c e l l s to check that a l l 45 choices have been recorded and as a check for the addition of sub-totals. I f t h i s t o t a l i s other than 45 re-check additions and scoring. C. Scoring the "sequence formula" t h i s i s a set of four derived scores which are obtained by examining the occurrence of d i f f e r e n t c olors over the three pyramids i n each series. Inspect the color frequency l i n e s (e.g. Bed, Orange, et c . ) . Count the number of l i n e s containing non-zero entries i n columns I, II and III and enter the number of such l i n e s i n c e l l CS (Constant Sum). Count the number of li n e s with a non^zero entry i n only one of the three columns and enter in Mas (Sum of Maximal Change). Count the number of l i n e s with no non-zero entry and enter i n AS (Avoidance Sum). Add the entries for a l l c e l l s to check that they t o t a l ten. D. Scoring the "color syndorme" certain color combinations, c a l l e d "color syndromes" have been found to be of p a r t i c u l a r i n t e r p r e t i v e s i g n i f i c a n c e and are therefore scored routinely. Scoring consists of adding the raw frequencies of the colors contained in the o f f s e t t o t a l c e l l s i n column T of the record blank as follows: Normal syndrome (Nsyn) - Bed, green and blue Stimulation sydrome (Ssyn) - Bed, orange and yellow 97 Drive syndrome (Dsyn) - Yellow, green and brown Achromatic syndrome (Asyn) - White, gray and black The instructions provided i n paragraphs a. through d. are now repeated for the ugly pyramids. C O L O R P Y R A M I D T E S T - R E C O R D B L A N K Name: Joe Doe Age: 14 Education: 6th grade Occupation: Student Pretty 53 so. us 1 3 - 4 4 9 32 9 Sequence: CS M i S MnS AS Figure 3 a I n m T 11 2 i 3 12 i i 2 13 3 i i 4 14 Red 2 4 3 ' 1 21 1 1 1 3 ?2 2 Orango 1 3 i 5 1 31 1 1 2 32 1 I 1 3 Yellow 1 2 41 1 1 ' 42 1 I 2 43 1 I 2 44 1 1 Greco 3 1 3 ' ' I 51 52 1 2 1 4 53 1 1 '54 1 1 Blue 2 2 2 01 (2 1 ' 1 63 . 2 2 Purple 3 ' 1 71 1 1 2 72 1 1 2 Brown 2 2 4 While 8 0 Grey 9 1 3 4 Black 0 1 2 Syndromes: N S D A 22 | 19 | It | 6 | File No. 0001 Tested by: KWS Ugly 22 22 22 22 22. 22 Str.9S 71 14 9 71 71 Sir. 8L 42 42 42 72 0 a 0 72 CS Sequence: M i S MaS AS 1 » | > 1 I 11 in T 11 3 1 4 12 13 4 4 14 I 1 Red 3 2 < 9 '21 1 1 22 5 1 6 Orange 5 2 7 31 1 32 Yellow 0 41 1 1 42 2 3 5 43 44 Green 2 ! 1 3 6 1 51 i 1 52 4 4 53 54 2 2 Blue 5 2 7 | 61 62 63 2 2 Purple 2 1 | . 71 3 1 4 72 2 2 Brown 3 3 6 While 8 2 2 Crcy 9 1 I Black 0 . 2 3 5 Syndromes: S D Figure 3 b APPENDIX II Colour Pyramid Test Weighted Score Scales Appendix II Colour Pyramid Scales (Weighted Colour Scores) 1. considerate - inconsiderate 22. 2. calm - excitable 23. 3. energetic - t i r e d 24. 4. quiet - noisy 25. 5. patient - impatient 26. 6. cheerful - solemn 27. 7. f r i e n d l y - reserved 28. 8. mediative - unquestioning 29. 9. co-operative - obstructive 30. 10. happy - sad 31. 11. s e n s i t i v e - tough 32. 12. i n t e l l i g e n t - stupid 33. 13. poised - f l u s t e r e d 34. 14. tolerant - jealous 35. 15. dominant - submissive 36. 16. relaxed - tense 37. 17. conventional - unconventional 38. 18. sociable - self-contained 39. 19. t r u s t f u l - suspicious 40. 20. s e l f - e f f a c i n g - e g o t i s t i c a l 41. 21. conscientious - unscrupulous 42. (from Schaie and Heiss, 1964) adventurous - timid stable - unstable perservering - q u i t t i n g modest - attention-seeking open - defensive refine d - crude imaginative - p r a c t i c a l obedient - disobedient adaptable - i n f l e x i b l e responsible - i r r e s p o n s i b l curious - incurious t a l k a t i v e - s i l e n t carefree - anxious t a s t e f u l - i n a r t i s t i c resourceful - b a f f l e d independent - dependent adult - naive orderly - d i s o r d e r l y easygoing - i r r i t a b l e expressive - secretive brave - complaining APPENDIX III Correlation between Age, A b i l i t i e s , Personality, and Colour Vision Variables The following i s the key to va r i a b l e names: Name Variable Name Al Age A21 16 PF N A2 Verbal (V) A22 0 A3 Numerical (N) A23 ^1 A4 S p a t i a l (S) A24 Q 2 A5 Speed of Closure(Cs) A25 ^3 A6 Perceptual Speed (P) A26 ^4 A7 F l e x i b i l i t y of Closure (Cf) A27 CAT Blue A8 Associative Memory (Ma) A28 CAT Red A9 Span Memory (Ms) A29 CAT Green A10 Aiming (A) A30 CAT Yellow A l l 16 PF A A31 CAT Time A12 B A32 BCMT A13 C A3 3 100-Hue A14 E A3 4 RGMR A15 F A35 RGMMP A16 G A36 YBMR A17 H A3 7 YBMMP A18 I A38 GBMR A19 L A3 9 GBMMP A20 M NAME A l A 2 A 3 A4 A 5 A 6 A 7 Atl A 9 M E A N S 2 C . 7 7 5 1 2 C . C 3 1 5 1 4 . 3 3 9 7 4 6 . 5 7 C C 1 1 . et 53 4 1 . 3 1 3 b 1 C . C 4 4 6 8 . 5 1 2 7 9 5 5 . 1 9 1 7 S i t ) . D E V . C O R R E L A T I O N S AL. A 2 2 . 8 2 9 6 C 3 . 0 9 2 9 8 3 . 6 2 6 9 3 l . c c o o 0 . 2 C 7 9 0 . 1 4 3 9 1 , 1 1 . 3 2 / 4 3 . 6 8 4 4 5 9 . 0 4 0 6 7 - C . 1 3 4 5 0 . 0 . 0 2 2 5 0 , - 0 . C 1 1 9 - C . 2 . 5 0 2 4 7 3 . 5 4 2 3 3 8 . 1 8 1 0 4 i 1 2 9 2 2 4 6 0 3 6 1 0 . C 3 8 8 0 . 0 4 3 7 0 . 0 5 6 2 0 . 2 6 9 0 0 . 1 2 6 8 0 . 2 C 3 2 _A3_ 1 2 6 7 1 . 0 0 0 0 0 . 3 0 5 1 0 . 3 8 9 2 0 . 4 3 8 2 1 5 6 . O B S E R V A T I O N S _A4_ JL5 _ A6 -AX. 1 . 0 0 0 0 0 . 2 9 4 9 0 . 3 6 9 5 1 . 0 0 0 0 0 . 2 3 8 0 0 . 2 2 7 2 0 . 2 9 1 2 0 . 2 0 5 2 1 . 0 0 0 0 _£2_ _A.10_ JV.12-0 . 2 4 1 3 0 . 2 0 1 8 0 . 1 4 8 2 0 . 2 7 7 7 0 . 2 2 8 8 0 . 3 7 1 8 0 . 2 2 5 5 0 . 1 8 6 5 0 . 1 8 5 6 1 . 0 0 0 0 0 . 1 3 8 6 0 . 1 7 0 7 00 0 0 19 5 4 1 . 0 0 0 0 A 1 0 A l l A 1 2 A 1 3 A 1 4 A 1 5 A 1 6 A 1 7 - A - U L A 1 9 A 2 0 A 2 1 A 2 2 -A 2 3 A 2 4 A 2 5 A 2 6 A 2 7 A 2 6 A 2 9 A 3 0 A 3 1 A 3 2 A 3 3 A 3 4 A 3 5 A 3 o A 3 7 A 3 8 A 3 9 4 5 . 7 1 1 0 9 . 6 3 4 5 8 8 . 9 1 0 2 2 1 5 . 4 1 0 2 14 . 9 2 9 5 1 5 . 6 4 7 4 1 0 . 7 3 C 7 14 . 3 5 8 9 1 1 . 1 1 5 3 9 . 0 3 84 3 14 . 2 2 4 3 7 . 7 3 7 1 4 9 . 6 6 6 6 2 1 C . 9 4 2 3 U . 6 4 1 C I C . 8 2 0 5 1 2 . 9 3 5 9 1 9 . 7 8 7 9 16 . 4 6 C 4 1 6 . 0 7 6 5 16 . 6 7 2 6 4 2 . 7 9 7 5 2 5 . 9 C 9 7 1 1 C . 7 3 7 7 2 . 7 3 0 2 3 6 . 2 8 7 9 6 6 . 6 4 6 9 37 . 3 9 1 7 6 4 . C S 5 5 3 7 . 4 6 5 3 9 . 2 7 9 69 2 . 1 8 0 7 4 1 . 9 9 4 72 3 . 9 7 5 5 1 3 . 9 5-8 C I 4 . 5 2 3 4 8 2 . 6 1 2 4 1 5 . 3 C 6 C 2 3 . 7 9 1 2 5 3 . 6 4 1 8 2 3 . 6 0 5 o 7 2 . 6 9 7 9 2 4 . C 5 8 1 6 2 . 9 8 6 4 9 2 . 2 6 2 5 7 3 . 3 5 1 4 1 5 . 3 5 4 1 2 2 . 6 7 5 6 C 4 . 1 4 4 9 1 3 . 1 3 0 5 5 4 . 3 1 8 2 4 1 4 . 4 3 9 7 6 . 8 2 6 2 1 2 6 . 0 3 1 9 1 . 6 1 9 6 5 1 . 3 5 3 6 5 9 . 9 3 7 6 5 3 . 8 2 7 24 1 C . 6 5 6 9 2 . 6 1 4 1 1 - 0 . 0 5 2 1 - 0 . 2 6 3 6 0 . 0 6 5 0 0 . G 1 0 5 - 0 . 0 7 4 0 - 0 . 1 2 1 7 0 . 0 1 4 3 - 0 . 0 6 2 4 0 . 3 2 0 4 0 . 1 C 7 5 0 . 1 6 6 7 - 0 . 0 7 7 1 0 . 1 3 9 0 0 . 0 1 0 3 0 . 2 5 2 1 - 0 . 0 0 2 1 0 . 0 6 6 8 - 0 . 0 5 5 6 - C . C 1 1 6 - C . 0 1 9 1 - C . 1 l G J 0 . 2 7 5 6 - 0 . 1 0 7 2 0 . 1 9 2 7 0 . 2 3 0 6 0 . 0 9 2 6 - 0 . 0 0 9 4 0 . 2 7 3 4 - 0 . 0 8 5 7 0 . 2 5 9 9 0 . 0 4 6 1 0 . 1 4 8 4 - 0 . 0 1 1 4 - 0 . 1 1 6 9 0 . 1 7 1 9 0 . 0 4 6 3 2 3 C 8 0 2 6 4 2 C 8 2 0 . 2 8 5 5 0 . 1 0 1 6 0 . 0 0 3 4 0 . 0 5 9 9 0 . 0 7 9 6 - 0 . 0 6 7 0 0 . 1 7 6 1 0 . - 0 . 0 6 2 0 0 . 0 . 2 9 2 9 0 . 0 . 0 9 3 5 - 0 . 0 . 0 2 3 8 0 . - 0 . 0 7 1 0 - 0 . 0 . 0 5 1 3 - 0 . 0 5 2 6 - 0 . 1 0 5 2 17 7 0 O i 9 6 17 9 1 Oi 0 5 03 71 Oa 8 3 0 , - 0 . 0 . - 0 . 0 6 4 5 0 . 0 7 8 8 - 0 . 1 8 3 3 1 2 3 3 0 2 1 1 1 5 6 0 0 . C 0 2 5 0 . 1 1 2 8 - 0 . 0 1 1 2 - 0 . 1 1 6 2 - 0 . O C 1 5 0 . 1 3 2 7 1 . 0 0 0 0 0 . 0 0 8 6 0 . 1 3 6 3 0 . 0 8 2 3 0 . 0 0 8 9 - 0 . 0 1 2 4 - 0 . 1 7 6 2 - 0 . 0 6 1 8 0 . 1 5 9 6 0 8 6 4 4 6 0 4 0 4 G 7 0 . 0 8 9 5 - 0 . 0 1 0 7 - 0 . 0 1 5 6 1 . 0 0 0 0 0 . 0 2 0 2 - 0 . C 6 4 1 0 . 1 1 2 2 0 . 2 7 0 3 - 0 . 1 2 5 0 - 0 . 0 8 0 9 0 . 0 0 9 0 1 . 0 0 0 0 0 . 1 1 0 4 0 . 1 6 7 5 0 . 0 3 7 9 0 . 0 1 0 2 - 0 . 0 0 2 4 - 0 . 1 1 3 5 0 . - 0 . 0 . - 0 . 0 1 9 6 0 . 0 2 4 8 - 0 . 0 6 7 1 - 0 . 0 6 C 3 0 . 2 2 7 2 0 . 1 9 1 7 0 . 0 0 8 6 0 . 1 4 0 2 - 0 . 0 2 5 0 - 0 . 0 9 0 7 0 . 0 2 8 9 - 0 . 1 6 0 3 - 0 . 0 5 7 5 0 . 0 . 1 2 8 3 - 0 . - 0 . 0 9 4 8 - 0 . 0 . 0 6 7 1 - 0 . 0 1 4 2 - 0 . C 4 8 C - 0 . 0 6 9 8 0 . 1 0 0 1 0 . 0 2 1 3 - 0 . 1 1 0 2 0 . 0 2 9 4 0 . 0 2 3 4 1 5 6 6 Oo 1 0 3.2 A 5 00 8 0 01 8 7 00 5 4 - 0 . 0 4 7 5 0 . 0 8 0 2 0 . 0 0 7 8 - 0 . 1 0 3 2 - 0 . 0 3 9 1 _ Q J L 0 5 3 2 - . 0 . 0 0 1 5 0 . 0 3 2 7 - 0 . 0 9 9 1 0 . 0 5 6 9 0 . 0 9 2 7 0 . 0 9 2 8 . - 0 . 0 1 2 8 0 . 1 5 8 5 - 0 . 0 1 4 6 - 0 . 1 2 8 9 0 . 0 2 9 1 C . 0 5 2 3 - 0 . 1 2 9 7 - 0 . 0 6 3 4 - U . 0 5 9 8 0 . 0 7 8 3 - 0 . 1 5 2 7 0 . 0 0 0 1 - 0 . 0 7 1 6 0 . 0 5 1 5 - C . C 7 8 9 0 . i 5 5 0 - 0 . 1 6 9 9 0 . 1 6 4 8 - 0 . 0 3 6 0 0 . 0 . 0 9 7 9 - 0 . 0 . 1 5 2 1 0 . 0 . 1 6 8 2 0 . 2 3 9 1 J3_. 2 1 8 1 0 . 0 5 7 5 0 . 0 4 2 6 0 . C 2 1 1 0 1 4 2 08 0 7 l i 4 6 - 0 . 0 4 5 9 0 . 0 2 3 4 0 . 0 2 4 6 0 . 0 9 77 - 0 . 1 4 4 7 - 0 . 0 1 1 6 0 . 0 5 7 2 0 . 0 4 5 7 - 0 . 0 3 2 1 - 0 . 0 8 13 - 0 . 0 5 1 3 0 . 0 9 1 5 0 . 0 0 8 6 0 . 0 6 1 2 0 . 1 5 5 6 - 0 . 0 9 3 8 0 . 1 5 3 6 _ C . G 3 8 9 „ 0 . 1 0 2 6 0 . 2 4 5 9 - 0 . 1 9 6 2 0 . 0 . 0 . 0 . 1 2 2 1 0 . 1 5 6 8 0 . 1 4 1 4 l J 1 8 02 0 8 09 6 6 0 . C 9 6 7 C . 0 5 8 0 0 . C 6 0 3 0 . 3 2 3 4 0 . 0 6 8 4 0 . 2 7 5 5 0 . 0 9 2 1 0 . 0 2 3 3 0 . 1 0 3 5 0 . 0 7 5 7 . 1 8 4 1 . 1 7 7 8 0 . U l 0 6 0 . 1 5 9 1 0 . 3 2 4 2 0 . 0 3 5 1 0 . 2 4 5 0 0 . 2 8 5 5 - 0 . 1 8 6 5 0 . 0 4 9 8 - 0 . 0 4 0 0 - 0 . 0 0 7 0 0 . 1 1 2 6 0 . 2 1 4 6 0 . 0 6 8 7 • 0 . 0 1 6 9 0 . 0 6 0 2 0 . 0 6 7 1 0 . 0 7 4 4 0 . 0 4 9 9 - 0 . 0 4 2 7 0 . 0 4 3 8 0 . 1 7 3 6 0 . 0 5 2 0 0 . 0 1 8 5 - 0 . 0 1 1 2 • 0 ^ 3 8 . 0 3 1 3 . 2 0 8 8 0 . 0 2 8 4 0 . 0 . 1 3 9 2 0 . 0 . 1 9 2 3 0 . 0 . 0 6 9 4 - 0 . 0 0 9 0 0 . 0 0 2 6 - 0 . 3 6 3 C - 0 . 0 8 3 4 - 0 . C 2 5 2 0 . 2 1 9 0 0 . 0 3 6 9 0 . 1 3 0 2 O J 0 6 42 0 8 22 8 6 - 0 . 0 6 1 3 0 . 0 0 6 0 - 0 . 0 5 9 1 0 . 0 8 0 4 - 0 . 0 2 2 2 0 . 0 3 2 7 0 . 1 0 9 7 C . 2 3 6 4 0 . 2 3 3 9 - 0 . 0 4 0 3 - 0 . 0 1 6 2 0 . 0 9 7 1 0 . 1 1 0 1 - 0 . 1 5 9 4 0 . 1 2 6 1 0 . 0 6 4 5 0 . 0 3 5 1 _ - 0 _ . 3 8 2 0 0 . 0 6 1 0 0 . 1 C 4 3 - 0 . 1 2 0 9 - 0 . 0 4 8 4 0 . 2 4 6 0 „ - 0 . 0 1 4 9 _ - 0 . 0 4 3 0 - 0 . 0 8 3 3 0 . 0 3 7 9 0 . 1 1 5 0 - 0 . 0 9 7 6 0 . 0 5 4 9 - C . 0 4 C 6 0 . 1 6 2 2 - C . 0 7 8 9 0 . 0 8 0 7 • G . 0 8 5 8 0 . 0 4 0 3 0 . 1 8 0 4 - 0 . 0 1 1 6 J L . 0 5 9 6 0 . 1 0 5 8 0 . 1 1 0 3 0 . 2 0 4 1 0 . 0 0 7 7 0 . 0 0 0 1 - 0 . 0 9 1 9 0 . 0 0 9 3 0 . 1 4 7 4 0 . 0 0 7 4 0 . 0 7 4 6 0 . - 0 . 1 2 2 9 0 . __0._0741 0 . 15 8 0 U 2 9 2±3_C_ - 0 . 1 2 8 0 - 0 . C 6 5 2 _ 0 . 1 2 8 9 - 0 . 1 6 4 7 - 0 . 1 3 2 6 - 0 . 0 5 2 4 0 . 0 5 4 8 0 . 0 5 1 1 0 . 0 1 4 1 0 . 0 1 6 5 0 . 0 5 1 6 - 0 . 0 0 1 8 ' - 0 . 0 0 6 6 0 . 0 . 0 3 0 6 0 . - 0 . 1 1 3 3 0 . 22 19 20 6 3 l o 7 4 0 . 1 3 4 4 - 0 . 1 3 7 9 -_-0-!_09 5 3 _ 0 . 0 8 9 5 0 . 1 0 9 2 0 . 0 3 1 7 0 . 1 6 9 1 0 . 0 2 7 5 3 . 2 7 5 4 0 . 1 1 6 4 0 . 3 3 6 6 0 . 1 8 2 9 0 . 1 5 3 5 C . 1 1 1 7 __0..Q812_ 0 . 0 5 2 7 0 . 1 6 7 1 0 . 1 3 9 1 0 . C C 4 6 - 0 . 0 5 2 5 _o_._C3_oe_ - 0 . 0 2 3 8 0 . C I 0 6 - 0 . 0 2 U C . 1 9 6 ~ l ' - 0 . 0 8 1 2 G_.2 5 9 4 _ 0 . 1 4 3 7 1 0 . 2 3 2 9 P> . 1 0 4 2 C 0 * S ' E ' L A T I C N S ( C C N U M J E C ) A13_ A 1 4 A 1 5 A 1 6 A 1 3 A l ! A 1 6 A 1 7 A 1 8 A 1 9 A 2 0 A 2 1 A 2 2 A 2 3 A 2 4 A 2 5 A 2 6 127 A 1 7 A i e - A . i . ' L A 20 A 2 1 A 2 2 C 9 4 5 l . C C C C C I 4 9 C . 3 1 2 5 1 . C C C 0 J 3 9 C - C . 1 i 6 4 — C • 1 1 2 1 0 a 0 . - 0 . - 0 . 2 8 ^ 2 0 6 3 2 4 0 1 7 3 4 6 4 1 Q 2 4 5 7 2 9 C . 3 2 S 4 0 . 4 4 1 8 C . 1 C 4 6 C . 0 4 9 0 " 4.16 0 0 . 2 6 ; 2 . . C . C 2 1 9 - C . 1 8 4 2 • C . 0 5 3 9 l . C C C C C . 1 7 C 6 - 0 . 2 6 1 6 0 . C 7 4 C A 2 3 A 2 4 A 2 5 _ A 2 0 A 2 7 A 2 8 - C . 0 1 4 4 - C . 2 1 5 3 ^.•_Q4_8 7_ - C . 1 5 6 8 C . 0 0 9 9 - C . 1 0 1 1 l . C C C C C . 1 2 4 6 1 . J L i 0 7 _ 3 7 _ j ! 0 . 0 . 0 8 9 5 0 . 2 8 4 6 0 . 1 7 11 . 2 3 2 1 0 , . 2 7 8 2 0 , . 3 5 7 5 - C , 0 3 0 0 _C_8J=L6_ 4 0 3 0 . 0 6 5 4 CU6*7 0 . C 8 6 0 0 . 2 8 9 3 - 0 . 5 9 77 0 . 0 6 6 5 0 . 16 £ 4 . 1 C 2 4 . 2 9 C 3 - C . 3 5 6 2 - 0 . 2 C 8 9 - C . 1 5 5 7 _C . 5 1 77 _ 1 _ . A 0 H 0 _ - 0 . 0 8 4 2 - 0 . 1 0 0 7 0 . 3 7 5 0 0 . 1 4 77 - C . 1 3 9 8 C . C 2 4 9 C . 2 5 1 3 0 . - 0 . 2 2 7C - C . • 0 . 0 0 9 4 - C . 0 0 2 3 1 0 9 8 i 9 0 3 • 0 • 0 2 4 6 - C . 1 C 2 3 C . 0 5 5 6 0 . 1 7 1 6 - 0 . 1 3 2 9 - 0 . 3 0 9 2 . 0 0 0 0 . 1 5 2 4 1 . 0 0 0 0 . 3 0 3 5 0 . 1 2 1 6 1 . 0 0 0 0 A 2 9 A 3 0 A - J L A 3 2 A 3 3 A 3 4 0 . U } 3 C . 0 1 8 8 * 0 • C6 6 3 C . C 3 C 6 - 0 . C 8 0 9 - C . C 2 C 9 -C . 0 4 5 9 C . 0 0 0 5 C . 0 5 6 1 - 0 . 3 1 2 1 0 . - 0 . 2 0 2 8 0 . C O 7 6 9 - 0 . 0 1 7 2 0 4 3 4 0 6 2 3 0 . 0 3 1 8 0 . L 3 3 3 0 . 0 3 6 3 - 0 . C 9 6 9 - C . C 7 5 0 C . C 6 9 5 0 . 0 1 2 J C . 0 r ; 6 5 - J . 0 5 3 1_ - 0 , - C . 1 3 34 C . 0 6 C 1 •0 . 0 0 5 1 0 . 4 3 3 2 - 0 0 . 0 3 5 3 . 0 • 0 . 0 4 9 5 0 0 . 0 3 7 9 0 . • 0 . 0 3 5 4 - o . • C . 0 5 4 6 - 0 . A 3 5 A 3 n A 3 7 A 3 b A 3 9 ! 5 9 7 - 0 . 0 9 ?9 C . G C 2 0 0 9 3 3 0 2 4 9 0 3 2 3 0 . C 3 6 5 -. C 8 9 7 C . C 6 3 7 •_01i_2 - C . C 9 9 5 C . C C 8 2 C . 0 3 5 9 • C . 0 2 7 9 - 0 . 0 4 78 0 - 0 . 0 5 5 8 0 - 0 . 0 0 8 4 - 0 .'C 4 o 1 - 0 . 0 3 • 0 . 1 2 3 8 - 0 . • C . 0 8 7 7 - 0 . • 0 . 0 1 2 7 - 0 . 0 0 8 8 0 6 3 1. 0 1 6 0 0 . 0 0 4 6 0 . 0 . 0 1 1 7 0 , 0 . 1 6 1 5 0 , . 3 1 2 2 - 0 . 3 8 8 6 0 . 0 0 5 3 1 . 0 0 0 C . 0 1 9 0 - 0 . 0 1 3 7 - 0 . 0 6 8 1 0 . 0 5 6 8 1 . . 0 7 0 1 0 . 1 4 6 0 - 0 . 4 0 5 7 - 0 . C 9 1 3 0 , . 2 6 1 9 0 . 0 8 9 5 0 . 6 2 2 0 - 0 . 0 7 9 7 - 0 , • 1 4 3 3 0 . 0 4 0 5 0 . 0 0 1 3 0 . 0 2 9 5 0 . . 1 3 4 0 - 0 . 0 2 3 2 - 0 . 1 9 6 0 0 . 1 6 4 9 0_. . 1 8 4 2 - 0 . 1 0 3 0 - 0 . 0 3 3 0 0 . 1 0 4 7 0 . . 0 4 4 5 0 . 1 7 7 0 - 0 . 0 7 4 0 - 0 . 1 0 8 5 - 0 . . 0 5 6 1 - 0 . 0 . 3 1 0 0 . 0 6 4 7 - 0 . 0 7 0 7 0 . 0 0 0 0 0 76 7 1 1 8 5 2 2 2 8 J U O O Q J L - 0 . 3 8 1 8 0 . 0 5 9 7 0 . 1 4 5 1 1 . 0 0 0 0 - 0 . 0 3 0 2 - 0 . 2 8 6 7 0 1 7 9 0 . 0 7 8 9 0 . 0 2 8 0 - 0 . 0 5 6 9 oV 0 9 3 4 0 . 0 0 9 0 0 . 0 2 0 7 G . 0 6 7 4 0 . 0 6 6 8 - 0 . 0 6 0 6 0 . U 7 8 0 . 0 4 8 8 0 . 0 9 1 2 1 3 3 8 1 6 4 2 0 . C . 0 3 6 S C . 1 C 7 0 . 1C.IS C . 1 3 6 ? 0 . 0 8 8 6 C . 0 3 6 2 . 0 4 0 5 0 . 1 2 7 7 C . 0 6 O 6 0 . 0 0 7 1 C Q P P , E L A n c r . S < C C N 1 I M l E C ) 1 " - ' i 1 2 - U - ' J i ) ^ 0 - 2 7 1 0 - 0 . 0 2 4 6 0 . 1 6 3 1 0 . 0 2 1 1 - 0 . 0 5 8 9 0 . ^ . 0 6 3 c C . 1 5 4 9 - 0 . 0 0 6 1 0 . 0 4 3 5 0 . 1 1 7 8 - 0 . 1 8 6 6 - 0 . 0 4 3 4 - 0 . 0 2 0 ' 0 . - C i 0 7 3 0 0 ^ 0 6 3 2 0 . 0 7 9 7 - 0 . 0 6 7 7 Q . Q 9 8 1 - 0 . 1 4 3 6 - 0 . 0 8 0 1 - n ^ n S j l 0 . 0 . 1 0 1 5 0 . 0 0 8 7 0 . 1 2 6 6 0 . 1 6 6 . 3 - 0 . 1 8 J 9 - 0 . 0 6 1 3 O . C 1 5 8 0 . 1 3 6 1 0 . 0 0 9 4 0 . 0 4 3 6 0 . 0 9 1 8 - 0 . 1 0 1 7 - 0 . 1 0 1 0 - 0 . 0 6 3 7 1 8 3 9 1 5 4 8 0 4 2 7 0 . 0 2 6 4 0 . 2 3 7 1 : J 3 . _ ? ' * 1 4 0 . 1 1 0 4 0 . 0 9 6 0 0 . 0 0 2 9 - 0 . 0 1 0 6 - 0 . 0 8 4 1 - 0 . 0 5 4 0 _ - 0 . 0 3 1 1 - 0 . 1 2 2 3 0 . 0 9 3 9 C . 1 0 1 0 1 4 6 9 0 5 5 2 _ 1 2 2 0 0 1 8 6 0 . 1 3 9 5 0 . 0 5 4 6 .J).tS>33.Q_ 0 . 0 4 8 9 0 . 0 5 9 3 1 . 0 0 0 0 _0 « p 9 5 2 _ 6". 2 8 8 5 0 . 2 2 4 9 _0_. 1 6 8 2 _ 6 . 1 6 6 9 0 . 2 0 9 3 0 . 0 5 5 4 0 . 0 2 6 6 - 0 . 0 1 3 6 : 0 . . 0 - 0 82__ 0 . - 0 2 5 5 C . 0 2 5 0 0 . 1 6 73 0 . 0 0 5 5 0 . 0 1 7 3 0 . 0 3 1 8 - 0 . 0 2 3 4 A 2 8 A 2 9 A 3 0 A 3 1 A 3 2 A 3 6 A 3 7 A 3 8 1 . 0 . 0 . o c . A 2 6 C C C C i e c i 1 7 3 9 C 8 5 5 1 6 5 1 4 2 9 . C C C C . 1 C 9 7 . 1 3 C 4 . C 5 1 3 A 3 3 0 . A 3 4 0 . A 3 5 0 . 2 i c . 8 • C .1 1 4 8 2 t 4 5 ' C . 1 9 1 1 0.0.12 C . 1 C 4 3 0 . 0 . 1 9 1 3 1 5 4 3 2 1 8 8 C . C 6 8 9 C . C 5 7C C . 1 2 5 9 A 3 9 0 . E X E C U T I O N 0 5 3 3 C . C 7 3 C T E R M I N A T E C A 3 C 1 « C o w 0 0 . 0 1 5 3 0 . 1 8 1 1 0 . 1 3 3 1 C . 1 £ £4 0 . 06 54 A 3 1 . C C C C . 0 0 1 2 C . 1 C 3 9 C . 1 5 1 3 C . 1 2 5 3 C . 1 C 6 7 C . 0 4 6 7 _C_i_0fc84 A 3 2 1 . 0 0 0 0 A 3.3 A 3 4 C . 0 9 8 2 C . 0 2 0 6 C . 1 1 5 1 0 . 3 5 2 3 0 . 1 6 5 2 C . 1 4 7 3 C . 1 1 1 5 0 . 0 6 9 7 : . 2 1 1 8 1 . 0 0 0 0 C . 3 8 8 6 0 . 0 6 3 0 C . 3 2 6 9 0 . 1 4 7 8 0 . 3 2 4 5 C . 1 9 6 7 - C . 0 1 5 5 C . 1 6 3 0 0 . 1 5 5 9 . 1 . 0 0 0 0 0 . 4 2 5 3 0 . 2 5 1 7 0 . 4 6 0 9 A 3 5 A 3 6 1 . 0 0 0 0 C . 0 1 7 9 0 . 0 0 7 8 - 0 . 0 1 3 6 1 . 0 0 0 0 0 . 7 4 9 6 0 . 7 5 3 2 A 3 7 A 3 8 A 3 9 1 . 0 0 0 0 0 . 5 2 7 9 1 . 0 0 0 0 0 . 2 5 9 7 0 . 0 5 3 5 0 . 5 7 6 7 0 . 4 3 4 9 0 T 6 I 8 3 T . 0 0 0 0 

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            data-media="{[{embed.selectedMedia}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
https://iiif.library.ubc.ca/presentation/dsp.831.1-0094141/manifest

Comment

Related Items