by Paul W. Egeler M.S.

This package provides functions relating to power and sample size calculation for the CMH test. There are also several helper functions for interconverting probability, odds, relative risk, and odds ratio values.

The **Cochran-Mantel-Haenszel test** (CMH) is an inferential test for the association between two binary variables, while controlling for a third confounding nominal variable. Two variables of interest, *X* and *Y*, are compared at each level of the confounder variable *Z* and the results are combined, creating a common odds ratio. Essentially, the CMH test examines the *weighted* association of *X* and *Y*. The CMH test is a common technique in the field of biostatistics, where it is often used for case-control studies.

Given a target power which the researcher would like to achieve, a calculation can be performed in order to estimate the appropriate number of subjects for a study. The `power.cmh.test`

function calculates the required number of subjects per group to achieve a specified power for a Cochran-Mantel-Haenszel test.

Researchers interested in estimating the probability of detecting a true positive result from an inferential test must perform a power calculation using a known sample size, effect size, significance level, *et cetera*. The `power.cmh.test`

function can compute the power of a CMH test, given parameters from the experiment.

Installation of the CRAN release can be done with `install.packages()`

. From the R console:

`install.packages("samplesizeCMH")`

Downloading and installing the latest version from GitHub is facilitated by `devtools`

. To do so, type the following into your R console:

```
install.packages("devtools")
devtools::install_github("pegeler/samplesizeCMH")
```

- Download from CRAN at

https://cloud.r-project.org/package=samplesizeCMH - Browse source code at

https://github.com/pegeler/samplesizeCMH - Report a bug at

https://github.com/pegeler/samplesizeCMH/issues

- Paul Egeler

Author, maintainer - All authors...