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htestClust (version 0.2.2)

Reweighted Marginal Hypothesis Tests for Clustered Data

Description

A collection of reweighted marginal hypothesis tests for clustered data, based on reweighting methods of Williamson, J., Datta, S., and Satten, G. (2003) . The tests in this collection are clustered analogs to well-known hypothesis tests in the classical setting, and are appropriate for data with cluster- and/or group-size informativeness. The syntax and output of functions are modeled after common, recognizable functions native to R. Methods used in the package refer to Gregg, M., Datta, S., and Lorenz, D. (2020) , Nevalainen, J., Oja, H., and Datta, S. (2017) Dutta, S. and Datta, S. (2015) , Lorenz, D., Datta, S., and Harkema, S. (2011) , Datta, S. and Satten, G. (2008) , Datta, S. and Satten, G. (2005) .

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Version

Install

install.packages('htestClust')

Monthly Downloads

180

Version

0.2.2

License

MIT + file LICENSE

Maintainer

Mary Gregg

Last Published

May 18th, 2022

Functions in htestClust (0.2.2)

icsPlot

Test of Marginal Proportion for Clustered Data
cortestClust

Test for Marginal Association Between Paired Clustered Data
levenetestClust

Reweighted Levene's Test for Homogeneity of Variance in Clustered Data
screen8

Example data for informative cluster size
chisqtestClust

Chi-squared Test for Clustered Count Data
mcnemartestClust

Test of Marginal Homogeneity for Clustered Data
onewaytestClust

Test for Equal Marginal Means in Clustered Data
ttestClust

Test of Marginal Means in Clustered Data
icstestClust

Test for Informative Cluster Size
proptestClust

Test of Marginal Proportion for Clustered Data
vartestClust

Reweighted Test to Compare Two Variances in Clustered Data
wilcoxtestClust

Rank Sum and Signed Rank Tests for Clustered Data