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Investigating differential options functioning based on multinomial logistic regression with widely used statistical software

University of British Columbia

This thesis focuses on an investigation of differential functioning in all options of multiple-choice items, referred to as differential options functioning (DOF). That is, DOF investigates whether respondents from different groups (i.e., subpopulations), with equal levels of attribute being measured, would have different probabilities to select the options. In previous research, DOF has been typically conducted as a secondary analysis for DIF of items in achievement/aptitude tests. This thesis introduces how DOF can provide fruitful information in various psychological and educational measurement contexts. In addition, this thesis proposes a set of integrated and straightforward procedures for investigating DOF based on the known theories of multinomial logistic regression. A demonstration is provided to guide the application of the proposed method.

Text

2017-08-18

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/62712

Measurement, Evaluation and Research Methodology

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/