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corTest  

Robust Tests for Equal Correlation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("corTest", "1.0.7")



Attach the package and use:
library("corTest")
Maintained by
Danyang Yu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-06-14
Latest Update: 2020-09-25
Description:
There are 6 novel robust tests for equal correlation. They are all based on logistic regressions. The score statistic U is proportion to difference of two correlations based on different types of correlation in 6 methods. The ST1() is based on Pearson correlation. ST2() improved ST1() by using median absolute deviation. ST3() utilized type M correlation and ST4() used Spearman correlation. ST5() and ST6() used two different ways to combine ST3() and ST4(). We highly recommend ST5() according to the article titled ''New Statistical Methods for Constructing Robust Differential Correlation Networks to characterize the interactions among microRNAs'' published in Scientific Reports. Please see the reference: Yu et al. (2019) .
How to cite:
Danyang Yu (2018). corTest: Robust Tests for Equal Correlation. R package version 1.0.7, https://cran.r-project.org/web/packages/corTest. Accessed 06 Jun. 2026.
Previous versions and publish date:
0.9.6 (2018-06-14 20:37), 0.9.7 (2019-02-11 09:03), 0.9.8 (2019-03-11 09:42), 1.0.0 (2020-05-23 16:00), 1.0.4 (2020-07-19 16:40)
Other packages that cited corTest R package
View corTest citation profile
Other R packages that corTest depends, imports, suggests or enhances
Complete documentation for corTest
Functions, R codes and Examples using the corTest R package
Some associated functions: construct_network . es . fisher_transfer_test . genEset . generate_data . ghdist . plotDiffCor . st1 . st2 . st3 . st4 . st5 . st6 . 
Some associated R codes: corTest.R . data.R . genEset.R . plotDiffCor.R .  Full corTest package functions and examples
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