PTAM 2025

ABSTRACTS

Discrimination between types of common systematic variation in data contaminated by method effects using CFA models
Karl Schweizer

Abstract:In data contaminated by method effects, common systematic variation is inhomogeneous requiring that attribute-related common systematic variation is in structural investigations discriminated from other variation. In the reported study, CFA measurement models dealing differently with such inhomogeneity were compared with respect to their performance in investigating data contaminated by either speededness or high subset homogeneity. For this purpose, structured random data with five different levels of speededness respectively subset-homogeneity were generated and investigated. The investigations were conducted by the one-factor congeneric and tau-equivalent CFA models, as well as the bifactor CFA model designed as mixture of tau-equivalent and fixed-links models. In data with speededness the congeneric model indicated good model fit while the tau-equivalent model showed sensitivity for the effect. In data with subset-homogeneity both models showed sensitivity. Only the bifactor model accounted for the common systematic variation and discriminated well between the attribute and method effects.

Keywords: comfirmatory factor analysis, discrimination, speededness, subset homogeneity, method effect

Correspondence:
Karl Schweizer, Institute of Psychology, Goethe University Frankfurt, Theodor-W.-Adorno-Platz 6, 60323 Frankfurt a. M., Germany. K.Schweizer@psych.uni-frankfurt.de