How to quantify the evidence for the absence of a correlation

Abstract

We present a suite of Bayes factor hypothesis tests that allow researchers to grade the decisiveness of the evidence that the data provide for the presence versus the absence of a correlation between two variables. For concreteness, we apply our methods to the recent work of Donnellan et al. (in press) who conducted nine replication studies with over 3,000 participants and failed to replicate the phenomenon that lonely people compensate for a lack of social warmth by taking warmer baths or showers. We show how the Bayes factor hypothesis test can quantify evidence in favor of the null hypothes

Abstract by Eric‐Jan Wagenmakers; Josine Verhagen; Alexander Ly, Behavior Research Methods (2015) — licensed CC BY 4.0.

Related failures