Diagnosing Response Style Behavior by Means of a Latent-Class Factor Approach. Socio-Demographic Correlates of Gender Role Attitudes and Perceptions of Ethnic Discrimination Reexamined

By G. Moors. 2003

80 citations recorded by the source corpus.

Subfields: Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/7bd20caaddb86c241f5de321643b173ca56d012a

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In Sociology and Political Science

Citations in the corpus

Response Styles in Survey Research: A Literature Review of Antecedents, Consequences, and Remedies (2013, methodology): “Moors, G. (2003). Diagnosing response style behavior by means of a latent-class factor approach. Socio-demographic correlates of gender role attitudes and perceptions of ethnic discrimination reexamined. Quality & Quantity, 37, 277-302. Moors, G. (2008). Exploring the effect of a middle response cat”
Addressing Score Bias and Differential Item Functioning Due to Individual Differences in Response Style (2009, methodology): “A similar interpretation has emerged with other self-report measures when using latent class approaches to the study of response style such that the first dimension represents the intended-to-be-measured trait and the second an ERS dimension (Eid & Rauber, 2000; Moors, 2003, 2004).”
Multiscale Measurement of Extreme Response Style (2011, methodology): “The approach presented in this article is perhaps most similar to a method presented by Moors (2003, 2004) that represents response style differences between respondents in the form of latent classes using a multinomial logistic model.”
Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches (2011, background): “To the extent that agreement tendency is associated with cultural background it is prone to be one of the factors that can cause measurement inequivalence in the cross-cultural comparisons (Moors, 2003; Billiet and McClendon, 2000).”
Latent Class Analysis (2021, background): “…as one of the DFactors may represent the factor of interest, while the others correspond to nuisance factors that allow the meaningful factor to be measured without bias (as an example of how the DFactor model has been proven useful to adjust for response style behavior, see Moors, 2003).”