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cocotest  

Dependence Condition Test Using Ranked Correlation Coefficients
View on CRAN: Click here


Download and install cocotest package within the R console
Install from CRAN:
install.packages("cocotest")

Install from Github:
library("remotes")
install_github("cran/cocotest")

Install by package version:
library("remotes")
install_version("cocotest", "1.0.3")



Attach the package and use:
library("cocotest")
Maintained by
Jiangtao Gou
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-10
Latest Update: 2024-01-10
Description:
A common misconception is that the Hochberg procedure comes up with adequate overall type I error control when test statistics are positively correlated. However, unless the test statistics follow some standard distributions, the Hochberg procedure requires a more stringent positive dependence assumption, beyond mere positive correlation, to ensure valid overall type I error control. To fill this gap, we formulate statistical tests grounded in rank correlation coefficients to validate fulfillment of the positive dependence through stochastic ordering (PDS) condition. See Gou, J., Wu, K. and Chen, O. Y. (2024). Rank correlation coefficient based tests on positive dependence through stochastic ordering with application in cancer studies, Technical Report.
How to cite:
Jiangtao Gou (2024). cocotest: Dependence Condition Test Using Ranked Correlation Coefficients. R package version 1.0.3, https://cran.r-project.org/web/packages/cocotest
Previous versions and publish date:
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Functions, R codes and Examples using the cocotest R package
Some associated functions: coco1 . coco2 . 
Some associated R codes: RcodeC1.R . RcodeC2.R .  Full cocotest package functions and examples
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