Pattern Heterogeneity via Distributional Differences Across Contingency Tables

Statistical hypothesis testing of pattern heterogeneity via differences in underlying distributions across two or more contingency tables. Three tests are included: the comparative chi-squared test (Song et al, 2014) (Zhang et al, 2015) , the Sharma-Song test, and the heterogeneity test. 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. These options test for 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.


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0.0.2 by Joe Song, a month ago

Browse source code at

Authors: Ruby Sharma [aut] , Joe Song [aut, cre]

Documentation:   PDF Manual  

LGPL (>= 3) license

Imports Matrix

Suggests Ckmeans.1d.dp, FunChisq, knitr, rmarkdown, testthat

See at CRAN