Some practical reasons for reconsidering the Kolmogorov‐Smirnov test

Wilcox, Rand R.

doi:10.1111/j.2044-8317.1997.tb01098.x

Cited by 58Probability and Statistical ResearchStatistical Distribution Estimation and ApplicationsAdvanced Statistical Methods and Models

Some practical reasons for reconsidering the Kolmogorov‐Smirnov test

Wilcox, Rand R.·1997·British Journal of Mathematical and Statistical Psychology

DOI 10.1111/j.2044-8317.1997.tb01098.x

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Abstract

The Kolmogorov‐Smirnov test is a method for comparing the distributions of two independent groups that has virtually disappeared from applied research and introductory statistics books for the social sciences. The apparent reason is the perception that it has low power compared to methods for comparing means in particular and measures of location in general. However, extant studies comparing the power of the Kolmogorov‐Smirnov test to other methods for comparing means are limited to normal distributions having a common variance. This note points out that, even under a shift model, the Kolmogorov‐Smirnov test not only can have high power relative to methods for comparing robust measures of location, there are situations where it has higher power than methods for comparing robust measurement of location. Some additional features of the Kolmogorov‐Smirnov test are noted, and a simple S‐PLUS program for computing the exact significance level is provided. Data from a study on the effects of drinking alcohol are used to illustrate the potential advantage of the Kolmogorov‐Smirnov test.

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The Kolmogorov-Smirnov two-sample test is a nonparametric way to examine two sets of data and determines the probability that they were drawn from the same distribution, without making any assumptions about what those distributions might be.
“The KS test is a nonparametric way to examine two sets of data and determines the probability that they were drawn from the same distribution, without making any assumptions about what those distributions might be.”
From Disambiguation of social polarization concepts and measures (2016) · cites this paper as Wilcox, 1997

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Authors: Wilcox, R. R.
Affiliations: University of Southern California (US)
Corresponding author: Wilcox, Rand R.
ORCID: Wilcox, Rand R.
Venue: British Journal of Mathematical and Statistical Psychology
Publisher: Wiley
Published: 1997-05
Volume: 50
Issue: 1
Pages: 9-20
ISSN: 0007-1102 (ISSN-L)
2044-8317
DOI: 10.1111/j.2044-8317.1997.tb01098.x
OpenAlex: W2089809176
Cited by: 58
References: 0
Citations by year: 2025: 3 · 2024: 4 · 2023: 1 · 2022: 6 · 2021: 5 · 2020: 4 · 2019: 2 · 2018: 3 · 2017: 3 · 2016: 3 · 2015: 2 · 2014: 5 · 2013: 2 · 2012: 2
FWCI: 0.47
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor, 5208 d)
Locations: British Journal of Mathematical and Statistical Psychology (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Keywords: Kolmogorov-Smirnov test, statistical power, distribution comparison, shift model, nonparametric tests, alcohol effects

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Some practical reasons for reconsidering the Kolmogorov‐Smirnov test

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