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IsingFit - Fitting Ising Models Using the ELasso Method

This network estimation procedure eLasso, which is based on the Ising model, combines l1-regularized logistic regression with model selection based on the Extended Bayesian Information Criterion (EBIC). EBIC is a fit measure that identifies relevant relationships between variables. The resulting network consists of variables as nodes and relevant relationships as edges. Can deal with binary data.

Last updated 1 years ago

6.85 score 10 stars 5 dependents 25 scripts 1.9k downloads

NetworkComparisonTest - Statistical Comparison of Two Networks Based on Several Invariance Measures

This permutation based hypothesis test, suited for several types of data supported by the estimateNetwork function of the bootnet package (Epskamp & Fried, 2018), assesses the difference between two networks based on several invariance measures (network structure invariance, global strength invariance, edge invariance, several centrality measures, etc.). Network structures are estimated with l1-regularization. The Network Comparison Test is suited for comparison of independent (e.g., two different groups) and dependent samples (e.g., one group that is measured twice). See van Borkulo et al. (2021, in press; the final article will be available, upon publication, via its DOI: 10.1037/met0000476).

Last updated 3 years ago

5.07 score 70 scripts 1.1k downloads