Automatically report the results of Bayesian model comparison using the loo package.
# S3 method for compare.loo
report(x, include_IC = TRUE, include_ENP = FALSE, ...)Objects of class report_text().
An object of class brms::loo_compare.
Whether to include the information criteria (IC).
Whether to include the effective number of parameters (ENP).
Additional arguments (not used for now).
The rule of thumb is that the models are "very similar" if |elpd_diff| (the
absolute value of elpd_diff) is less than 4 (Sivula, Magnusson and Vehtari, 2020).
If superior to 4, then one can use the SE to obtain a standardized difference
(Z-diff) and interpret it as such, assuming that the difference is normally
distributed. The corresponding p-value is then calculated as 2 * pnorm(-abs(Z-diff)).
However, note that if the raw ELPD difference is small (less than 4), it doesn't
make much sense to rely on its standardized value: it is not very useful to
conclude that a model is much better than another if both models make very
similar predictions.