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 $H_0: phi <= delta$.


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install.packages("PAsso")

0.1.10 by Xiaorui (Jeremy) Zhu, a month ago


GitHub: https://github.com/XiaoruiZhu/PAsso


Report a bug at https://github.com/XiaoruiZhu/PAsso/issues


Browse source code at https://github.com/cran/PAsso


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