Psychological Methods· 2018Q1
A tutorial on regularized partial correlation networks.
- 2,773citations
- Q1SCImago
- 2018year
Short summary
This tutorial introduces regularized partial correlation networks, a popular method for modeling direct relationships between psychological variables, and demonstrates their estimation and interpretation.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces partial correlation networks for modeling direct psychological variable relationships.
- Explains how regularization aids in estimating parsimonious and interpretable network structures.
- Provides practical guidance for R implementation and an empirical example.
- Discusses hyperparameter tuning, handling non-normal data, and sample size determination.
AI-generated from the title and abstract; the full text is not read.
Abstract
Recent years have seen an emergence of network modeling applied to moods, attitudes, and problems in the realm of psychology. In this framework, psychological variables are understood to directly affect each other rather than being caused by an unobserved latent entity. In this tutorial, we introduce the reader to estimating the most popular network model for psychological data: the partial correlation network. We describe how regularization techniques can be used to efficiently estimate a parsimonious and interpretable network structure in psychological data. We show how to perform these analyses in R and demonstrate the method in an empirical example on posttraumatic stress disorder data. In addition, we discuss the effect of the hyperparameter that needs to be manually set by the researcher, how to handle non-normal data, how to determine the required sample size for a network analysis, and provide a checklist with potential solutions for problems that can arise when estimating regularized partial correlation networks. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
The authors' abstract, as published at the source. Psychological Methods, 2018 · DOI ↗
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Field: Experimental and Cognitive Psychology
Experimental and Cognitive PsychologyPsychology