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To remove the influence of spuriously long response times, many investigators compute "restricted means", obtained by throwing out any response time more than 2.0, 2.5, or 3.0 standard deviations from the overall sample average. Because reaction time distributions are skewed, however, the computation of restricted means introduces a bias: the restricted mean underestimates the true average of the population of response times. This problem may be very serious when investigators compare restricted means across conditions with different numbers of observations, because the bias increases with sample size. Simulations show that there is substantial differential bias when comparing conditions with fewer than 10 observations against conditions with more than 20. With strongly skewed distributions and a cutoff of 3.0 standard deviations, differential bias can influence comparisons of conditions with even more observations.
Jeff Miller (Fri,) studied this question.