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
2018-01-01

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).
2018
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: https://hdl.handle.net/11590/399682
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