Assessing the Partial Association Between Ordinal Variables

An implementation of the unified framework for assessing partial association between ordinal variables after adjusting for a set of covariates (Dungang Liu, Shaobo Li, Yan Yu and Irini Moustaki (2020), accepted by the Journal of the American Statistical Association). This package provides a set of tools to quantify, visualize, and test partial associations between multiple ordinal variables. It can produce a number of $phi$ measures, partial regression plots, 3-D plots, and $p$-values for testing $H_0: phi=0$ or $H_0: phi <= delta$.


Reference manual

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0.1.10 by Xiaorui (Jeremy) Zhu, 4 months ago


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Authors: Xiaorui (Jeremy) Zhu [aut, cre] , Shaobo Li [aut] , Dungang Liu [ctb, aut] , Yuejie Chen [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports VGAM, copBasic, pcaPP, methods, foreach, MASS, GGally, gridExtra, utils, progress, plotly, copula

Depends on stats, ggplot2, dplyr

Suggests doParallel, tidyverse, goftest, faraway, ordinal, rms, testthat, mgcv, PResiduals, knitr, rmarkdown, truncdist

Linking to Rcpp

See at CRAN