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A Nonlinear Dynamic Latent Class Structural Equation Model


Kelava, Augustin; Brandt, Holger (2019). A Nonlinear Dynamic Latent Class Structural Equation Model. Structural Equation Modeling, 26(4):509-528.

Abstract

In this article, we propose a nonlinear dynamic latent class structural equation modeling (NDLC-SEM). It can be used to examine intra-individual processes of observed or latent variables. These processes are decomposed into parts which include individual- and time-specific components. Unobserved heterogeneity of the intra-individual processes are modeled via a latent Markov process that can be predicted by individual- and time-specific variables as random effects. We discuss examples of sub-models which are special cases of the more general NDLC-SEM framework. Furthermore, we provide empirical examples and illustrate how to estimate this model in a Bayesian framework. Finally, we discuss essential properties of the proposed framework, give recommendations for applications, and highlight some general problems in the estimation of parameters in comprehensive frameworks for intensive longitudinal data.

Abstract

In this article, we propose a nonlinear dynamic latent class structural equation modeling (NDLC-SEM). It can be used to examine intra-individual processes of observed or latent variables. These processes are decomposed into parts which include individual- and time-specific components. Unobserved heterogeneity of the intra-individual processes are modeled via a latent Markov process that can be predicted by individual- and time-specific variables as random effects. We discuss examples of sub-models which are special cases of the more general NDLC-SEM framework. Furthermore, we provide empirical examples and illustrate how to estimate this model in a Bayesian framework. Finally, we discuss essential properties of the proposed framework, give recommendations for applications, and highlight some general problems in the estimation of parameters in comprehensive frameworks for intensive longitudinal data.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Scopus Subject Areas:Social Sciences & Humanities > General Decision Sciences
Physical Sciences > Modeling and Simulation
Social Sciences & Humanities > Sociology and Political Science
Social Sciences & Humanities > General Economics, Econometrics and Finance
Uncontrolled Keywords:Modelling and Simulation, General Economics, Econometrics and Finance, General Decision Sciences, Sociology and Political Science
Language:English
Date:4 July 2019
Deposited On:13 Jan 2020 13:17
Last Modified:29 Jul 2020 13:06
Publisher:Taylor & Francis
ISSN:1070-5511
OA Status:Closed
Publisher DOI:https://doi.org/10.1080/10705511.2018.1555692

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