ic_weights: Compare Information Criteria

In cjvanlissa/tidySEM: Tidy Structural Equation Modeling

Compare Information Criteria

Description

IC weights quantify the evidence in favor of different models in a set. This function normalizes the IC values to obtain IC weights, which sum to 1. The model with the highest weight is most supported by the data. The ratio of different weights gives the relative support in favor of one model over another.

Usage

ic_weights(x, ...)

Arguments

x	An object for which a method exists.
...	Additional arguments.

Value

A list of class ic_weights with elements ⁠$weights⁠, which contains the model weights, and ⁠$comparison⁠, which contains the relative support in favor of each model over the others.

References

Wagenmakers, E. J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic bulletin & review, 11(1), 192-196. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3758/BF03206482")}

Examples

ics <- c(100, 200, 102, 300)
ic_weights(ics)

cjvanlissa/tidySEM documentation built on March 16, 2024, 6:35 a.m.