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Statistical Interpretation of Multiple Comparisons and Sample Size

Statistical Interpretation of Multiple Comparisons and Sample Size Abstract Sir.—Caution must be exercised in interpreting the results of the study by Miller and Strunk1 regarding the deaths of children that were due to asthma. Even if the control group was perfectly matched with the study group, statistical analysis of the results should take at least two factors into account: (1) The greater the number of comparisons undertaken, the more likely it is that a "significant" low P value will be found on the basis of chance alone.2 In the study by Miller and Strunk, at least 30 comparisons were made between the control and study groups. Six variables were noted to be different between the two groups at P<.05, but because of the problem of multiple comparisons this does not mean that the groups actually differed in these six variables. Methods to correct for multiple comparisons have been developed.2 For example, the conservative Bonferroni correction References 1. Miller BD, Strunk RC. Circumstances surrounding the deaths of children due to asthma . AJDC . 1989;143:1294-1299. 2. Ware JH, Mosteller F, Ingelfinger JA. P values . In: Bailar JC, Mosteller F, eds. Medical Uses of Statistics . Waltham, Mass: NEJM Books; 1986;149-169. 3. Freiman JA, Chalmers TC, Smith H, Kuebler RR. The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial . N Engl J Med . 1978;299:690-694.Crossref 4. Young MJ, Bresnitz EA, Strom BL. Sample size nomograms for interpreting negative clinical studies . Ann Intern Med . 1983;99:248-251.Crossref http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Diseases of Children American Medical Association

Statistical Interpretation of Multiple Comparisons and Sample Size

American Journal of Diseases of Children , Volume 144 (7) – Jul 1, 1990

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Publisher
American Medical Association
Copyright
Copyright © 1990 American Medical Association. All Rights Reserved.
ISSN
0002-922X
DOI
10.1001/archpedi.1990.02150310017014
Publisher site
See Article on Publisher Site

Abstract

Abstract Sir.—Caution must be exercised in interpreting the results of the study by Miller and Strunk1 regarding the deaths of children that were due to asthma. Even if the control group was perfectly matched with the study group, statistical analysis of the results should take at least two factors into account: (1) The greater the number of comparisons undertaken, the more likely it is that a "significant" low P value will be found on the basis of chance alone.2 In the study by Miller and Strunk, at least 30 comparisons were made between the control and study groups. Six variables were noted to be different between the two groups at P<.05, but because of the problem of multiple comparisons this does not mean that the groups actually differed in these six variables. Methods to correct for multiple comparisons have been developed.2 For example, the conservative Bonferroni correction References 1. Miller BD, Strunk RC. Circumstances surrounding the deaths of children due to asthma . AJDC . 1989;143:1294-1299. 2. Ware JH, Mosteller F, Ingelfinger JA. P values . In: Bailar JC, Mosteller F, eds. Medical Uses of Statistics . Waltham, Mass: NEJM Books; 1986;149-169. 3. Freiman JA, Chalmers TC, Smith H, Kuebler RR. The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial . N Engl J Med . 1978;299:690-694.Crossref 4. Young MJ, Bresnitz EA, Strom BL. Sample size nomograms for interpreting negative clinical studies . Ann Intern Med . 1983;99:248-251.Crossref

Journal

American Journal of Diseases of ChildrenAmerican Medical Association

Published: Jul 1, 1990

References