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

Tobias Koch (), Martin Schultze, Jana Holtmann, Christian Geiser and Michael Eid
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Tobias Koch: Leuphana Universität Lüneburg
Martin Schultze: Freie Universität Berlin
Jana Holtmann: Freie Universität Berlin
Christian Geiser: Utah State University
Michael Eid: Freie Universität Berlin

Psychometrika, 2017, vol. 82, issue 1, No 2, 17-47

Abstract: 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.

Keywords: latent state-trait (LST) theory; CFA-MTMM; multilevel structural equation modeling; structurally different methods; interchangeable methods (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11336-016-9541-x

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