Cochran–Mantel–Haenszel statistics

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In statistics, the Cochran–Mantel–Haenszel statistics are a collection of test statistics used in the analysis of stratified categorical data.[1] They are named after William G. Cochran, Nathan Mantel and William Haenszel.[2][3][4][5] One of these test statistics is the Cochran–Mantel–Haenszel (CMH) test, which allows the comparison of two groups on a dichotomous/categorical response. It is used when the effect of the explanatory variable on the response variable is influenced by covariates that can be measured/observed ("controlled for" to use common but somewhat misleading terminology). Unobserved covariates pose greater problems. It is often used in observational studies where random assignment of subjects to different treatments cannot be controlled, but influencing covariates can.

In the CMH test, the data are arranged in a series of associated 2 × 2 contingency tables, the null hypothesis is that the observed response is independent of the treatment used in any 2 × 2 contingency table. The CMH test's use of associated 2 × 2 contingency tables increases the ability of the test to detect associations (the power of the test is increased).[citation needed]

Notes

  1. SAS/STAT(R) 9.2 User's Guide Cochran-Mantel-Haenszel Statistics
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See also

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