In recent years, research in organizational psychology has witnessed a shift inattention from a mostly variable-focused approach, to a mostly person-focused approach. Indeed, it has been widely recognized that the study of a sample’s heterogeneity is a meaningful and necessary task of researchers dealing with human behavior in organizational contexts. As a consequence, there has been growing interest in the application of statistical analyses able to uncover latent sub-groups of individuals. The present contribution was conceived as a tutorial for the application of one of these statistical analyses, namely second-order growth mixture modeling, and to illustrate its inner links with concepts from non-linear dynamic models. Throughout the paper, we provided (a) a discussion on the relationships between growth mixture modeling and the cusp catastrophe model; (b) Mplus syntaxes and output excerpts of a longitudinal analysis conducted on job performance (N = 420 employees rated once a year for four consecutive years); (c) an overview of two important topics regarding the correct implementation of growth mixture modeling (i.e., optimal number of classes and local maxima).

Alessandri, G., Perinelli, E., De Longis, E., & Theodorou, A. (2018). Second-Order Growth Mixture Modeling in Organizational Psychology: An Application in the Study of Job Performance Using the Cusp Catastrophe Model. NONLINEAR DYNAMICS, PSYCHOLOGY AND LIFE SCIENCES, 22(1), 53.

Second-Order Growth Mixture Modeling in Organizational Psychology: An Application in the Study of Job Performance Using the Cusp Catastrophe Model

Theodorou Annalisa
2018

Abstract

In recent years, research in organizational psychology has witnessed a shift inattention from a mostly variable-focused approach, to a mostly person-focused approach. Indeed, it has been widely recognized that the study of a sample’s heterogeneity is a meaningful and necessary task of researchers dealing with human behavior in organizational contexts. As a consequence, there has been growing interest in the application of statistical analyses able to uncover latent sub-groups of individuals. The present contribution was conceived as a tutorial for the application of one of these statistical analyses, namely second-order growth mixture modeling, and to illustrate its inner links with concepts from non-linear dynamic models. Throughout the paper, we provided (a) a discussion on the relationships between growth mixture modeling and the cusp catastrophe model; (b) Mplus syntaxes and output excerpts of a longitudinal analysis conducted on job performance (N = 420 employees rated once a year for four consecutive years); (c) an overview of two important topics regarding the correct implementation of growth mixture modeling (i.e., optimal number of classes and local maxima).
Alessandri, G., Perinelli, E., De Longis, E., & Theodorou, A. (2018). Second-Order Growth Mixture Modeling in Organizational Psychology: An Application in the Study of Job Performance Using the Cusp Catastrophe Model. NONLINEAR DYNAMICS, PSYCHOLOGY AND LIFE SCIENCES, 22(1), 53.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/399682
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