In recent years, research in organizational psychology has witnessed a shift in attention from a mostly variable-focused approach, to a mostly person-focused approach. Indeed, it has been widely recognized that the study of worker’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 workers. 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).

Second-order growth mixture modeling in organizational psychology: An application in the study of job performance using the cusp catastrophe model / Alessandri, Guido; Perinelli, Enrico; De Longis, Evelina; Theodorou, Annalisa. - In: NONLINEAR DYNAMICS, PSYCHOLOGY AND LIFE SCIENCES. - ISSN 1090-0578. - STAMPA. - 22:1(2018), pp. 53-76.

Second-order growth mixture modeling in organizational psychology: An application in the study of job performance using the cusp catastrophe model

Perinelli, Enrico;
2018-01-01

Abstract

In recent years, research in organizational psychology has witnessed a shift in attention from a mostly variable-focused approach, to a mostly person-focused approach. Indeed, it has been widely recognized that the study of worker’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 workers. 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
1
Alessandri, Guido; Perinelli, Enrico; De Longis, Evelina; Theodorou, Annalisa
Second-order growth mixture modeling in organizational psychology: An application in the study of job performance using the cusp catastrophe model / Alessandri, Guido; Perinelli, Enrico; De Longis, Evelina; Theodorou, Annalisa. - In: NONLINEAR DYNAMICS, PSYCHOLOGY AND LIFE SCIENCES. - ISSN 1090-0578. - STAMPA. - 22:1(2018), pp. 53-76.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/277550
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