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April 11, 2022Psychological Methods1,445 citationsOpen Access

Comparing network structures on three aspects: A permutation test.

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CBClaudia D. van BorkuloRBRiet van BorkLBLynn Boschloo

Key Points

  • To introduce and evaluate the Network Comparison Test (NCT), a permutation-based resampling technique designed to assess structural invariance across independent psychological networks.
  • Developed a permutation testing framework to evaluate three specific properties: network structure invariance, edge strength invariance, and global strength invariance across two independent, cross-sectional datasets.
  • Conducted simulation studies to assess statistical power and Type I error rates across varying sample sizes and structural differences.
  • Demonstrated the empirical utility of the method by comparing depression symptom network structures between males and females.
  • Simulation analyses demonstrated that the Type I error rate remained close to the nominal significance level across all three test aspects.
  • Statistical power proved sufficiently high when sample sizes and effect differences between networks were substantial.
  • The empirical application successfully differentiated symptom connection patterns in male versus female depression datasets.

Abstract

Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Applications of such network approaches to various psychological constructs have recently moved from a descriptive stance, in which the goal is to estimate the network structure that pertains to a construct, to a more comparative stance, in which the goal is to compare network structures across populations. However, the statistical tools to do so are lacking. In this article, we present the network comparison test (NCT), which uses resampling-based permutation testing to compare network structures from two independent, cross-sectional data sets on invariance of (a) network structure, (b) edge (connection) strength, and (c) global strength. Performance of NCT is evaluated in simulations that show NCT to perform well in various circumstances for all three tests: The Type I error rate is close to the nominal significance level, and power proves sufficiently high if sample size and difference between networks are substantial. We illustrate NCT by comparing depression symptom networks of males and females. Possible extensions of NCT are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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Cite This Study

Borkulo et al. (2022) studied this question.

synapsesocial.com/papers/69509c300478236e9cbf8a47https://doi.org/10.1037/met0000476
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