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

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Authors

  • Tobias Koch
  • Martin Schultze
  • Jana Holtmann
  • Christian Geiser
  • Michael Eid
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.
OriginalspracheEnglisch
ZeitschriftPsychometrika
Jahrgang82
Ausgabenummer1
Seiten (von - bis)17-47
Anzahl der Seiten31
ISSN0033-3123
DOIs
PublikationsstatusErschienen - 01.03.2017

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© 2016, The Psychometric Society.

DOI