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The Use Of Analysis Of Covariance Structures For Comparing The Psychometric Properties Of Multiple Variables Across Populations

The Use Of Analysis Of Covariance Structures For Comparing The Psychometric Properties Of... It is common practice to assume that the dependent variables in differential prediction studies, and analysis of variance and co-variance designs are characterized by certain psychometric properties which are invariant across the subgroups of interest. More specifically, the accuracy of the results of such analyses depends on the assumption that the dependent variables are measuring the constructs in the same metrics with equivalent reliabilities across all subgroups. Systematic procedures are outlined for testing these assumptions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multivariate Behavioral Research Taylor & Francis

The Use Of Analysis Of Covariance Structures For Comparing The Psychometric Properties Of Multiple Variables Across Populations

The Use Of Analysis Of Covariance Structures For Comparing The Psychometric Properties Of Multiple Variables Across Populations

Multivariate Behavioral Research , Volume 13 (4): 16 – Oct 1, 1978

Abstract

It is common practice to assume that the dependent variables in differential prediction studies, and analysis of variance and co-variance designs are characterized by certain psychometric properties which are invariant across the subgroups of interest. More specifically, the accuracy of the results of such analyses depends on the assumption that the dependent variables are measuring the constructs in the same metrics with equivalent reliabilities across all subgroups. Systematic procedures are outlined for testing these assumptions.

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Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1532-7906
eISSN
0027-3171
DOI
10.1207/s15327906mbr1304_3
Publisher site
See Article on Publisher Site

Abstract

It is common practice to assume that the dependent variables in differential prediction studies, and analysis of variance and co-variance designs are characterized by certain psychometric properties which are invariant across the subgroups of interest. More specifically, the accuracy of the results of such analyses depends on the assumption that the dependent variables are measuring the constructs in the same metrics with equivalent reliabilities across all subgroups. Systematic procedures are outlined for testing these assumptions.

Journal

Multivariate Behavioral ResearchTaylor & Francis

Published: Oct 1, 1978

There are no references for this article.