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Conventional Wisdom on Measurement: A Structural Equation Perspective

Conventional Wisdom on Measurement: A Structural Equation Perspective The applicability of 5 conventional guidelines for construct measurement is critically examined: (a) Construct indicators should be internally consistent for valid measures, (b) there are optimal magnitudes of correlations between items, (c) the validity of measures depends on the adequacy with which a specified domain is sampled, (d) within-construct correlations must be greater than between-construct correlations, and (e) linear composites of indicators can replace latent variables. A structural equation perspective is used, showing that without an explicit measurement model relating indicators to latent variables and measurement errors, none of these conventional beliefs hold without qualifications. Moreover, a “causal” indicator model is presented that sometimes better corresponds to the relation of indicators to a construct than does the classical test theory “effect” indicator model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Psychological Bulletin American Psychological Association

Conventional Wisdom on Measurement: A Structural Equation Perspective

Psychological Bulletin , Volume 110 (2): 10 – Sep 1, 1991

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Publisher
American Psychological Association
Copyright
Copyright © 1991 American Psychological Association
ISSN
0033-2909
eISSN
1939-1455
DOI
10.1037/0033-2909.110.2.305
Publisher site
See Article on Publisher Site

Abstract

The applicability of 5 conventional guidelines for construct measurement is critically examined: (a) Construct indicators should be internally consistent for valid measures, (b) there are optimal magnitudes of correlations between items, (c) the validity of measures depends on the adequacy with which a specified domain is sampled, (d) within-construct correlations must be greater than between-construct correlations, and (e) linear composites of indicators can replace latent variables. A structural equation perspective is used, showing that without an explicit measurement model relating indicators to latent variables and measurement errors, none of these conventional beliefs hold without qualifications. Moreover, a “causal” indicator model is presented that sometimes better corresponds to the relation of indicators to a construct than does the classical test theory “effect” indicator model.

Journal

Psychological BulletinAmerican Psychological Association

Published: Sep 1, 1991

There are no references for this article.