DiffXTables: Pattern Analysis Across Contingency Tables

Statistical hypothesis testing of pattern heterogeneity via differences in underlying distributions across multiple contingency tables. Five tests are included: the comparative chi-squared test (Song et al. 2014) <doi:10.1093/nar/gku086> (Zhang et al. 2015) <doi:10.1093/nar/gkv358>, the Sharma-Song test, the heterogeneity test, the marginal-change test (Sharma et al. 2020), and the strength test (Sharma et al. 2020). Under the null hypothesis that row and column variables are statistically independent and joint distributions are equal, their test statistics all follow an asymptotically chi-squared distribution. A comprehensive type analysis categorizes the relation among the contingency tables into type null, 0, 1, and 2 (Sharma et al. 2020). They can identify heterogeneous patterns that differ in either the first order (marginal) or the second order (joint distribution deviation from product of marginals). Second-order differences may reveal more fundamental changes than first-order differences across heterogeneous patterns.

Version: 0.1.1
Depends: R (≥ 3.0), pander
Imports: Rdpack (≥ 0.6-1)
Suggests: Ckmeans.1d.dp, FunChisq, knitr, rmarkdown, testthat
Published: 2020-08-16
Author: Ruby Sharma ORCID iD [aut], Joe Song ORCID iD [aut, cre]
Maintainer: Joe Song <joemsong at cs.nmsu.edu>
License: LGPL (≥ 3)
NeedsCompilation: no
Citation: DiffXTables citation info
Materials: README NEWS
CRAN checks: DiffXTables results

Downloads:

Reference manual: DiffXTables.pdf
Vignettes: Using the 'DiffXTables' R package to detect heterogeneity
Package source: DiffXTables_0.1.1.tar.gz
Windows binaries: r-devel: DiffXTables_0.1.1.zip, r-release: DiffXTables_0.1.1.zip, r-oldrel: DiffXTables_0.1.1.zip
macOS binaries: r-release: DiffXTables_0.1.1.tgz, r-oldrel: DiffXTables_0.1.1.tgz
Old sources: DiffXTables archive

Reverse dependencies:

Reverse suggests: FunChisq

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