samplesizeCMH
Power and Sample Size Calculation for the Cochran-Mantel-Haenszel Chi-Squared Test
Science Score: 13.0%
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Low similarity (12.8%) to scientific vocabulary
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Repository
Power and Sample Size Calculation for the Cochran-Mantel-Haenszel Chi-Squared Test
Basic Info
- Host: GitHub
- Owner: pegeler
- Language: R
- Default Branch: master
- Homepage: https://pegeler.github.io/samplesizeCMH/
- Size: 1.33 MB
Statistics
- Stars: 4
- Watchers: 1
- Forks: 4
- Open Issues: 1
- Releases: 0
Topics
Metadata Files
README.md
samplesizeCMH: Sample Size Calculation for the Cochran-Mantel-Haenszel Test
by Paul W. Egeler M.S.
Description
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.
Please see the package website for more information on how this package is used, including documentation and vignettes.
The Cochran Mantel Haenszel Test
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.
Sample Size Calculation
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.
Power Calculation
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
Installation of the CRAN release can be done with install.packages(). From the R console:
r
install.packages("samplesizeCMH")
Downloading and installing the latest version from GitHub is facilitated by
remotes.
To do so, type the following into your R console:
r
if (!require("remotes")) install.packages("remotes")
remotes::install_github("pegeler/samplesizeCMH")
Owner
- Login: pegeler
- Kind: user
- Website: https://paul.egeler.us/
- Repositories: 3
- Profile: https://github.com/pegeler
Co-organizer of @WestMichiganRUserGroup and avid R user. Comments and posts on this site are my own and do not necessarily reflect the views of my employer.
GitHub Events
Total
- Delete event: 1
- Push event: 2
Last Year
- Delete event: 1
- Push event: 2
Packages
- Total packages: 1
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Total downloads:
- cran 246 last-month
- Total docker downloads: 11
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 2
- Total maintainers: 1
cran.r-project.org: samplesizeCMH
Power and Sample Size Calculation for the Cochran-Mantel-Haenszel Test
- Homepage: https://github.com/pegeler/samplesizeCMH
- Documentation: http://cran.r-project.org/web/packages/samplesizeCMH/samplesizeCMH.pdf
- License: GPL-2 | GPL-3
-
Latest release: 0.0.3
published about 2 years ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.4.0 depends
- stats * imports
- DescTools * suggests
- datasets * suggests
- knitr * suggests
- rmarkdown * suggests
- testthat * suggests