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Note. Built on train sample (N=21,899). Arrow thickness denotes a change in the Bayesian Information Criterion (BIC; a relative measure of a model’s goodness-of-fit) arising from the proportion of the averaged 10,000 bootstrapped networks wherein that arrow is removed from the network. In other words, the more an arrow contributes to the model fit, the thicker it is.
