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Commentary |

Correction for Multiple TestingCorrection for Multiple Testing: Is There a Resolution?

David L. Streiner, PhD, CPsych; Geoffrey R. Norman, PhD
Author and Funding Information

From the Department of Psychiatry and Behavioural Neurosciences (Dr Streiner) and the Department of Clinical Epidemiology and Biostatistics (Drs Streiner and Norman), McMaster University, Hamilton; and the Department of Psychiatry (Dr Streiner), University of Toronto, Toronto, ON, Canada.

Correspondence to: David L. Streiner, PhD, CPsych, Department of Psychiatry and Behavioural Neurosciences, McMaster University, Centre for Mountain Health Services, 100 W 5th St, Hamilton, ON, Canada, L8N 3K7; e-mail: streiner@mcmaster.ca


Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (http://www.chestpubs.org/site/misc/reprints.xhtml).


© 2011 American College of Chest Physicians


Chest. 2011;140(1):16-18. doi:10.1378/chest.11-0523
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In most studies, many statistical tests are performed. They can be run to compare the groups at baseline, look at relationships among the various measures, and, for intervention trials, examine more than one end point. As the number of tests increases, so does the probability of finding at least one of them to be statistically significant just by chance (the problem of multiplicity). A number of procedures have been developed to deal with multiplicity, such as the Bonferroni correction, but there is continuing controversy regarding if and when these procedures should be used. In this article, we offer recommendations about when they should and should not be brought into play.


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