Research Methods

Creating studies that are powered to detect the smallest effect of interest... without collecting more data than you need to detect bigger effects

A two-part blog post on outlier exclusion procedures, and their impact on false-positive rates.

How should researchers exclude outliers: Across the data, or within conditions? In this paper, I show that when outlier exclusions are performed in a way that is not 'blind' to the researchers' hypothesis (e.g., within conditions), they increase Type I error to unacceptable levels.