A Bayesian Multiverse Analysis of Many Labs 4: Quantifying the Evidence against Mortality Salience

Many Labs projects have become the gold standard for assessing the
replicability of key findings in psychological science. The Many Labs
4 project recently failed to replicate the mortality salience effect where
being reminded of one’s own death strengthens the own cultural identity. Here, we provide a Bayesian reanalysis of Many Labs 4 using
meta-analytic and hierarchical modeling approaches and model comparison with Bayes factors. In a multiverse analysis we assess the robustness of the results with varying data inclusion criteria and prior
settings. Bayesian model comparison results largely converge to a common conclusion: We find evidence against a mortality salience effect
across the majority of our analyses. Even when ignoring the Bayesian
model comparison results we estimate overall effect sizes so small (between d = 0.03 and d = 0.18) that it renders the entire field of mortality
salience studies as uninformative.