PAsso: 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 $H_0: phi <= delta$.

Version: 0.1.9
Depends: R (≥ 3.5.0), stats (≥ 3.5.0), ggplot2 (≥ 2.2.1), dplyr
Imports: VGAM, copBasic, pcaPP (≥ 1.9-73), methods, foreach (≥ 1.4.8), MASS (≥ 7.3-51.0), GGally, gridExtra, utils (≥ 3.5.3), progress (≥ 1.2.0), plotly, copula
LinkingTo: Rcpp
Suggests: doParallel (≥ 1.0.11), tidyverse, goftest, faraway, ordinal, rms, testthat, mgcv, PResiduals, knitr, rmarkdown, truncdist
Published: 2021-05-07
Author: Xiaorui (Jeremy) Zhu [aut, cre], Shaobo Li [aut], Dungang Liu [ctb, aut], Yuejie Chen [ctb]
Maintainer: Xiaorui (Jeremy) Zhu <zhuxiaorui1989 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: GitHub:
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: PAsso results


Reference manual: PAsso.pdf
Package source: PAsso_0.1.9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: PAsso_0.1.9.tgz, r-oldrel: PAsso_0.1.9.tgz
Old sources: PAsso archive


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