Stability and variability of personality networks. A tutorial on recent developments in network psychometrics

By G. Costantini, Juliette Richetin, E. Preti, E. Casini, Sacha Epskamp, Marco Perugini. Personality and Individual Differences, 2017

232 citations recorded by the source corpus.

Networks have been recently proposed for modeling dynamics in several kinds of psychological phenomena, such as personality and psychopathology. In this work, we introduce techniques that allow disentangling between-subject networks, which encode dynamics that involve stable individual differences, from within-subject networks, which encode dynamics that involve momentary levels of certain individual characteristics. Furthermore, we show how networks can be simultaneously estimated in separate groups of individuals, using a technique called the Fused Graphical Lasso. This technique allows also performing meaningful comparisons among groups. The unique properties of each kind of network are discussed. A tutorial to implement these techniques in the “R” statistical software is presented, together with an example of application.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/3fcf6ab7071b57a8d43a767c36bc285756f27efd

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In Cognitive Neuroscience

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Citations in the corpus

A Tutorial on Regularized Partial Correlation Networks (2016, methodology): “For a recent tutorial on this methodology, we refer the reader to Costantini et al. (2017).”