Literature DB >> 26790049

Measurement Invariance, Predictive Invariance, and the Duality Paradox.

R E Millsap.   

Abstract

The statistical literature on bias in psychological testing distinguishes at least two forms of bias: measurement bias and predictive bias. Measurement bias concerns group differences in the relationship between a test and the latent variable to be measured. Predictive bias concerns group differences in the relationship between a test and an external criterion. How are these two forms of bias related? For example. if a test is unbiased in the predictive sense, does this fact support the hypothesis that the test is unbiased in the measurement sense? A theorem is given that describes the conditions under which measurement invariance (lack of bias) is consistent with predictive invariance for the linear case. Paradoxically, these two forms of invariance are shown to be inconsistent under realistic conditions. This duality or inconsistency is illustrated in simulated data. The implications of the duality for group differences research are illustrated in real data involving gender and ethnic differences on the SAT. The phenomenon of duality may force a reinterpretation of common empirical findings of test criterion regression slope invariance. and of invariance in test validities. Other implications are discussed.

Year:  1995        PMID: 26790049     DOI: 10.1207/s15327906mbr3004_6

Source DB:  PubMed          Journal:  Multivariate Behav Res        ISSN: 0027-3171            Impact factor:   5.923


  6 in total

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Journal:  Psychometrika       Date:  2014-07       Impact factor: 2.500

3.  Integrative data analysis: the simultaneous analysis of multiple data sets.

Authors:  Patrick J Curran; Andrea M Hussong
Journal:  Psychol Methods       Date:  2009-06

4.  The consequences of ignoring measurement invariance for path coefficients in structural equation models.

Authors:  Nigel Guenole; Anna Brown
Journal:  Front Psychol       Date:  2014-09-17

5.  The Importance of Isomorphism for Conclusions about Homology: A Bayesian Multilevel Structural Equation Modeling Approach with Ordinal Indicators.

Authors:  Nigel Guenole
Journal:  Front Psychol       Date:  2016-03-02

6.  The Impact of Partial Measurement Invariance on Testing Moderation for Single and Multi-Level Data.

Authors:  Yu-Yu Hsiao; Mark H C Lai
Journal:  Front Psychol       Date:  2018-05-15
  6 in total

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