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Cited by 382

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Short Report: Reaction Time Analysis with Outlier Exclusion: Bias Varies with Sample Size

Miller, Jeff·1991·The Quarterly Journal of Experimental Psychology Section A

Abstract

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.

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Metadata

Authors
Miller, J.
Venue
The Quarterly Journal of Experimental Psychology Section A
Published
1991-11
Volume
43
Issue
4
Pages
907-912
ISSN
  • 0272-4987 (ISSN-L)
  • 1464-0740
OpenAlex
W2229267816
Cited by
382
References
12
FWCI
1.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Short Report: Reaction Time Analysis with Outlier Exclusion: Bias Varies with Sample Size. https://app.cochat.ai/papers/10.1080/14640749108400962
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Miller, J. (1991). Short Report: Reaction Time Analysis with Outlier Exclusion: Bias Varies with Sample Size. The Quarterly Journal of Experimental Psychology Section A. https://doi.org/10.1080/14640749108400962

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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