Quantifying the Reliability and Replicability of Psychopathology Network Characteristics.

ABSTRACT: Pairwise Markov random field networks-including Gaussian graphical models (GGMs) and Ising models-have become the "state-of-the-art" method for psychopathology network analyses. Recent research has focused on the reliability and replicability of these networks. In the present study, we compared the existing suite of methods for maximizing and quantifying the stability and consistency of PMRF networks (i.e., lasso regularization, plus the bootnet and NetworkComparisonTest packages in R) with a set of metrics for directly comparing the detailed network characteristics interpreted in the literature (e.g., the presence, absence, sign, and strength of each individual edge). We compared GGMs of depression and anxiety symptoms in two waves of data from an observational study

SUBMITTER: Forbes MK 

PROVIDER: S-EPMC6883148 | biostudies-literature | 2021 Mar-Apr

REPOSITORIES: biostudies-literature