A caveat on the Savage–Dickey density ratio: The case of computing Bayes factors for regression parameters

The Savage–Dickey density ratio is a simple method for computing the Bayes factor for an equality constraint on one or more parameters of a statistical model. In regression analysis, this includes the important scenario of testing whether one or more of the covariates have an effect on the dependent variable. However, the Savage–Dickey ratio only provides the correct Bayes factor if the prior distribution of the nuisance parameters under the nested model is identical to the conditional prior under the full model given the equality constraint. This condition is violated for multiple regression models with a Jeffreys–Zellner–Siow prior, which is often used as a default prior in psychology. Besides linear regression models, the limitation of the Savage–Dickey ratio is especially relevant when analytical solutions for the Bayes factor are not available. This is the case for generalized linear models, non-linear models, or cognitive process models with regression extensions. As a remedy, the correct Bayes factor can be computed using a generalized version of the Savage–Dickey density ratio.     

Age-related changes in materialism in adults – A self-uncertainty perspective

Materialism is the focus of much research due to its negative consequences for individuals and societies. While recent research indicates that the strength of materialistic value orientations changes with age during adulthood, little is known about the processes that cause these age-related changes. We propose that changes in materialism, as people grow older, are rooted in changes in self-uncertainty. We find evidence for this idea in two studies and across different measures of self-uncertainty. In addition, we show that the changes in materialism cannot be explained by (age-related) differences in socio-demographic variables. Finally, our results indicate that changes in self-uncertainty provide a better account for changes in materialism than age-related changes in self-esteem.     

False consensus in situational judgment tests: What would others do?

We introduce an alternative response instruction to reduce the fakability of situational judgment tests. This novel instruction is based on the false consensus effect, a robust social psychological bias whereby people infer that the majority of other people’s thoughts, attitudes, and behaviors are aligned with their own. In four studies, including both field and laboratory data (total N = 882), we demonstrate that participants show a false consensus bias when asked what others would do in situational judgment tests. Furthermore, the situational judgment test based on the false consensus effect turned out to relatively difficult to be fake, and produced scores that were meaningfully correlated with conceptually related traits, as well as both self-reported and behavioral outcomes.