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Network Model Trees

Author

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  • Jones, Payton J.
  • Mair, Patrick
  • Simon, Thorsten
  • Zeileis, Achim

Abstract

In many areas of psychology, correlation-based network approaches (i.e., psychometric networks) have become a popular tool. In this paper we define a statistical model for correlation-based networks and propose an approach that recursively splits the sample based on covariates in order to detect significant differences in the network structure. We adapt model-based recursive partitioning and conditional inference tree approaches for finding covariate splits in a recursive manner. This approach is implemented in the networktree R package. The empirical power of these approaches is studied in several simulation conditions. Examples are given using real-life data from personality and clinical research.

Suggested Citation

  • Jones, Payton J. & Mair, Patrick & Simon, Thorsten & Zeileis, Achim, 2019. "Network Model Trees," OSF Preprints ha4cw_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:ha4cw_v1
    DOI: 10.31219/osf.io/ha4cw_v1
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