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A Multimethod Latent State-Trait Model for Structurally Different And Interchangeable Methods

Published online by Cambridge University Press:  01 January 2025

Tobias Koch*
Affiliation:
Leuphana Universität Lüneburg
Martin Schultze
Affiliation:
Freie Universität Berlin
Jana Holtmann
Affiliation:
Freie Universität Berlin
Christian Geiser
Affiliation:
Utah State University
Michael Eid
Affiliation:
Freie Universität Berlin
*
Correspondence should be made to Tobias Koch, Leuphana Universität Lüneburg, Lüneburg, Germany. Email: tobias.koch@leuphana.de; URL: http://www.leuphana.de/zentren/methodenzentrum.html

Abstract

A new multiple indicator multilevel latent state-trait (LST) model for the analysis of multitrait–multimethod–multioccasion (MTMM-MO) data is proposed. The LST-COM model combines current CFA-MTMM modeling approaches of interchangeable and structurally different methods and LST modeling approaches. The model enables researchers to specify construct and method factors on the level of time-stable (trait) as well as time-variable (occasion-specific) latent variables and analyze the convergent and discriminant validity among different rater groups across time. The statistical performance of the model is scrutinized by a simulation study and guidelines for empirical applications are provided.

Information

Type
Original Paper
Copyright
Copyright © 2016 The Psychometric Society

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