Description: A set of functions used to compare co-occurrence between two corpora.
Imports: methods, stats, data.table (>= 1.9.6), RColorBrewer, rlist

Description: Identifies significant difference in co-occurrence counts for a given node or set of nodes across two corpora, using a Fisher’s Exact test.
Imports: methods, stats, data.table (>= 1.11.2), stringi, RColorBrewer,
Suggests: unittest, R.rsp, knitr, rmarkdown, lintr, testthat (>=

Title: Nonparametrics with clustered binary data
Description: This package implements non-parametric analyses for
clustered binary data. The elements of the cluster are assumed
exchangeable, and identical joint distribution (also known as
marginal compatibility, or reproducibility) is assumed for
clusters of different sizes. A trend test based on stochastic

clusters of different sizes.  A trend test based on stochastic

Title: Nonparametrics with clustered binary and multinomial data
Description: This package implements non-parametric analyses for clustered
binary data. The elements of the cluster are assumed exchangeable, and
identical joint distribution (also known as marginal compatibility, or
reproducibility) is assumed for clusters of different sizes. A trend test
based on stochastic ordering is implemented.

Title: Nonparametrics with Clustered Binary and Multinomial Data
Authors@R: person("Aniko", "Szabo", role=c("aut","cre"), email="aszabo@mcw.edu")
Imports: boot, combinat, geepack, dirmult, mvtnorm
binary and multinomial data. The elements of the cluster are assumed
exchangeable, and identical joint distribution (also known as marginal
compatibility, or reproducibility) is assumed for clusters of different
sizes. A trend test based on stochastic ordering is implemented.

Description: Implements non-parametric analyses for clustered

Title: Estimate Correlations Between Repeatedly Measured Endpoints
(E.g., Reliability) Based on Linear Mixed-Effects Models
Author: Wim Van der Elst, Geert Molenberghs, Dieter Hilgers, & Nicole Heussen
Maintainer: Wim Van der Elst <Wim.vanderelst@gmail.com>
Description: In clinical practice and research settings in medicine and the behavioral sciences, it is often of interest to quantify the correlation of a continuous endpoint that was repeatedly measured (e.g., test-retest correlations, ICC, etc.). This package allows for estimating these correlations based on mixed-effects models. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
BugReports: Wim Van der Elst <Wim.vanderelst@gmail.com>