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date: 23 February 2020

Abstract and Keywords

The chapter provides a comprehensive overview of classical approaches and recent advances in the latent variable modeling of person-situation data. It begins by reviewing the key concepts of latent state-trait (LST) theory (Steyer, Ferring & Schmitt, 1992; Steyer, Mayer, Geiser, & Cole, 2015), which is a measurement theory for measuring persons in situations. Subsequently, it discusses basic LST models for measuring (1) variability processes, (2) trait changes, and (3) method effects. The chapter presents a real data application of these basic models and subsequently discusses extensions of LST models to more complex designs for studying interaction effects between persons, situations, and methods, as well as models for categorical data and latent classes. The goal is to provide researchers with a systematic review of available models that can be applied to address substantive questions in single- and multimethod person-situation research.

Keywords: person-situation data, latent state-trait theory, multitrait-multimethod analysis, State variability, Trait changes, Person-situation interactions, Latent variable models, Longitudinal confirmatory factor analysis, Autoregressive effects

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