Science folk: what’s the current consensus on removing outliers? I’m hearing conflicting messages: (1) removing participants is bad but (2) having outliers is also bad. How do you personally screen for outliers? Current consensus on best practice?
Use robust metrics if possible eg median instead of mean. If not feasible, then I usually remove outliers based on visual inspection and report results with and without the outliers.
