Replicability and Generalisability in Face Research

Abstract

In this talk, I will discuss several initiatives to increase the replicability and generalisability of research on faces, with a special focus on big team science efforts, such as the Psychological Science Accelerator and ManyFaces. I will also make an argument for reproducible stimulus construction and introduce webmorphR, an R package for reproducibly scripting face stimulus creation. Additionally, I will explain how a common methodology in face research, the composite method, produces very high false positive rates, and explain alternatives to this, including the use of mixed effects models for analysing individual face ratings.