Time series of individual subjects have become a common data type in psychological
research. These data allow one to estimate models of within-subject dynamics, and thereby …

The use of idiographic research techniques has gained popularity within psychological
research and network analysis in particular. Idiographic research has been proposed as a …

Researchers in the field of network psychometrics often focus on the estimation of Gaussian
graphical models (GGMs)—an undirected network model of partial correlations—between …

We present the R package mgm for the estimation of k-order mixed graphical models
(MGMs) and mixed vector autoregressive (mVAR) models in high-dimensional data. These …

Network models are an increasingly popular way to abstract complex psychological
phenomena. While studying the structure of network models has led to many important …

Network analysis of ESM data has become popular in clinical psychology. In this approach,
discrete-time (DT) vector auto-regressive (VAR) models define the network structure with …

Objective: Recurrent depressive episodes are preceded by changing mean levels of
repeatedly assessed emotions (eg, feeling restless), which can be detected in real time …

Background Psychopathology research is changing focus from group-based “disease
models” to a personalized approach inspired by complex systems theories. This approach …

If psychopathology behaves like a complex dynamic system, sudden onset or worsening of
symptoms may be preceded by early-warning signals (EWSs). EWSs could thus reflect …

The aim of this chapter is to (a) provide a broad didactical treatment of the first-order
stochastic differential equation model—also known as the continuous-time (CT) first-order …