  Wilcoxon Rank-based tests are distribution-free alternatives to the popular
two-sample and paired t-tests. For independent data, they are available in
several R packages such as stats and coin. For clustered data, in spite of the
recent methodological developments, there did not exist an R package that makes
them available at one place. We present a package clusrank where the latest
developments are implemented and wrapped under a unified user-friendly
interface. With different methods dispatched based on the inputs, this package
offers great flexibility in rank-based tests for various clustered data. Exact
tests based on permutations are also provided for some methods. Details of the
major schools of different methods are briefly reviewed. Usages of the package
clusrank are illustrated with simulated data as well as a real dataset from an
ophthalmological study. The package also enables convenient comparison between
selected methods under settings that have not been studied before and the
results are discussed.
