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Comparison of the approaches to assessing statistical interactions : an application to risk factors for adolescent problem behaviour Rajlic, Gordana

Abstract

The purpose of the current project was to utilize and compare several approaches to assessing interactions among continuous variables. The approaches used in the project were: (a) multiple regression, (b) unconstrained mean-centered approach (Marsh, Wen, & Hau, 2004), (c) orthogonalizing approach (Little, Bovaird, & Widaman, 2006), and (d) latent moderated structural equations approach (LMS; Klein & Moosbrugger, 2000). The last three approaches utilize the latent variables modeling framework, and they address some of the limitations of multiple regression related to the assumption that the predictors are measured without error. All selected approaches were applied to a problem from psychology domain concerned with adolescent problem behaviour. Specifically, the interactions between certain risk factors relevant for adolescent delinquency (i.e., low self-control, family risk, and neighbourhood risk) were assessed. The International Youth Survey data collected from 3114 students in grades 7 to 9, in the city of Toronto, were utilized in the study. The results obtained by the different approaches were compared and their consistency was examined in terms of the existence, direction, and strength of the relations of interest (specifically, the statistical significance, sign, and magnitude of the obtained coefficients were examined, as well as the magnitude of the standard errors and model fit indices). According to the results of the comparison, there was a considerable consistency in the results of the different approaches. However, some differences were also noted. The obtained differences are of importance as they may affect researchers’ conclusions in regard to the substantive problems of interest. The current study provided a number of highlights that may be of interest to researchers focused on methodological as well as applied aspects of assessing interactions.

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Attribution-NonCommercial-NoDerivs 2.5 Canada