PSIS and WAIC perform similarly when applied to ordinary linear models. Important differences are found in model types where the distribution is not approximately normal or in the presence of observations that strongly influence the posterior.

CV and PSIS have higher variance as estimators of the KL divergence, while WAIC has greater bias.

PSIS has an advantage in warning the user when it is unreliable