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Cited by 1,037

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Hierarchically Nested Covariance Structure Models for Multitrait-Multimethod Data

Widaman, Keith F.·1985·Applied Psychological Measurement

Abstract

A taxonomy of covariance structure models for rep resenting multitrait-multimethod data is presented. Us ing this taxonomy, it is possible to formulate alternate series of hierarchically ordered, or nested, models for such data. By specifying hierarchically nested models, significance tests of differences between competing models are available. Within the proposed framework, specific model comparisons may be formulated to test the significance of the convergent and the discriminant validity shown by a set of measures as well as the ex tent of method variance. Application of the proposed framework to three multitrait-multimethod matrices al lowed resolution of contradictory conclusions drawn in previously published work, demonstrating the utility of the present approach.

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Metadata

Authors
Widaman, K. F.
Venue
Applied Psychological Measurement
Published
1985-03
Volume
9
Issue
1
Pages
1-26
ISSN
  • 0146-6216 (ISSN-L)
  • 1552-3497
OpenAlex
W2017897883
Cited by
1,037
References
3
FWCI
14.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Hierarchically Nested Covariance Structure Models for Multitrait-Multimethod Data. https://app.cochat.ai/papers/10.1177/014662168500900101
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Widaman, K. F. (1985). Hierarchically Nested Covariance Structure Models for Multitrait-Multimethod Data. Applied Psychological Measurement. https://doi.org/10.1177/014662168500900101

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