Nonlinear Dynamics, Psychology, and Life Sciences, Vol. 22, Iss. 1, January, 2018, pp. 53-76
@2018 Society for Chaos Theory in Psychology & Life Sciences

 
 
 

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

Guido Alessandri, Sapienza University of Rome, Italy
Enrico Perinelli, Sapienza University of Rome, Italy
Evelina De Longis, Sapienza University of Rome, Italy
Annalisa Theodorou, Sapienza University of Rome, Italy

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).

Keywords: second-order growth mixture modeling, GMM, job performance, person centered approach