人格
编码
理论(学习稳定性)
心理学
精神病理学
心理测量学
人工智能
认知心理学
机器学习
计算机科学
发展心理学
社会心理学
临床心理学
生物化学
基因
化学
作者
Giulio Costantini,Juliette Richetin,Emanuele Preti,Erica Casini,Sacha Epskamp,Marco Perugini
标识
DOI:10.1016/j.paid.2017.06.011
摘要
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.
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