1.2k citations · 1.7k across the 23 of their papers we have counts for
6 papers · 1 filter
Unidimensional factor models imply weaker partial correlations than zero-order correlations
Riet van Bork, Raoul P. P. P. Grasman, Lourens J. Waldorp
In a unidimensional factor model it is assumed that the set of indicators that loads on this factor are conditionally independent given the latent factor. Two indicators are, howev…
How well do Network Models predict Observations? On the Importance of Predictability in Network Models
Jonas Haslbeck, Lourens J Waldorp
Network models are an increasingly popular way to abstract complex psychological phenomena. While the study of the structure of network models has led to many important insights, l…
Mean field dynamics of graphs I: Evolution of probabilistic cellular automata for random and small-world graphs
Lourens J. Waldorp, Jolanda J. Kossakowski
It was recently shown how graphs can be used to provide descriptions of psychopathologies, where symptoms of, say, depression, affect each other and certain configurations determin…
Mean Field Dynamics of Graphs II: Assessing the Risk for the Development of Phase Transitions in Empirical Data
Jolanda J Kossakowski, Marijke CM Gordijn, Harriette Riese +1
Psychological disorders like major depressive disorder can be seen as complex dynamical systems. By looking at symptom activation patterns, we can investigate the dynamic behaviour…
The Gaussian Graphical Model in Cross-sectional and Time-series Data
Sacha Epskamp, Lourens J. Waldorp, René Mõttus +1
We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool. The GGM shows…
Network Psychometrics
Sacha Epskamp, Gunter K. J. Maris, Lourens J. Waldorp +1
This chapter provides a general introduction of network modeling in psychometrics. The chapter starts with an introduction to the statistical model formulation of pairwise Markov r…