Package: PAsso 0.1.11

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) <doi:10.1080/01621459.2020.1796394> 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.

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

PAsso_0.1.11.tar.gz
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PAsso.pdf |PAsso.html✨
PAsso/json (API)
NEWS

# Install 'PAsso' in R:
install.packages('PAsso', repos = c('https://xiaoruizhu.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/xiaoruizhu/passo/issues

Pkgdown site:https://xiaoruizhu.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • ANES2016 - The 2016 ANES Time Series Study with pre-election interview

On CRAN:

association-analysisordinal-variablespartial-associationstatisticscpp

4.14 score 7 stars 1 packages 13 scripts 150 downloads 8 exports 99 dependencies

Last updated 12 months agofrom:8a314aa79f. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 03 2025
R-4.5-win-x86_64NOTEJan 03 2025
R-4.5-linux-x86_64NOTEJan 03 2025
R-4.4-win-x86_64NOTEJan 03 2025
R-4.4-mac-x86_64NOTEJan 03 2025
R-4.4-mac-aarch64NOTEJan 03 2025
R-4.3-win-x86_64NOTEJan 03 2025
R-4.3-mac-x86_64NOTEJan 03 2025
R-4.3-mac-aarch64NOTEJan 03 2025

Exports:diagnostic.plotPAssoplot3DresidualsresidualsAcatresidualsVGAMsurrogatetest

Dependencies:ADGofTestaskpassbase64encbslibcachemclicodetoolscolorspacecopBasiccopulacpp11crayoncrosstalkcurldata.tabledigestdplyrevaluatefansifarverfastmapfontawesomeforcatsforeachfsgenericsGGallyggplot2ggstatsgluegoftestgridExtragslgtablehighrhmshtmltoolshtmlwidgetshttrisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelmomcoLmomentsmagrittrMASSMatrixmemoisemgcvmimemunsellmvtnormnlmenumDerivopensslpatchworkpcaPPpillarpkgconfigplotlyplyrprettyunitsprogresspromisespsplinepurrrR6randtoolboxrappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownrngWELLsassscalesstablediststringistringrsystibbletidyrtidyselecttinytexutf8vctrsVGAMviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
The 2016 ANES Time Series Study with pre-election interviewANES2016
Residual-based diagnostic plotsdiagnostic.plot diagnostic.plot.clm diagnostic.plot.default diagnostic.plot.glm diagnostic.plot.lrm diagnostic.plot.orm diagnostic.plot.PAsso diagnostic.plot.polr diagnostic.plot.resid
Partial association analysis between ordinal responses after adjusting for a set of covariatesPAsso
A matrix of partial regression plots between responses after adjustmentsplot plot.PAsso
3-D P-P plot and false color level plot for the inspection of the partial association analysisplot3D plot3D.default plot3D.PAsso
Print partial association matrixprint print.PAsso print.PAsso.test
Extract Model Residualsresiduals residuals,vgam-method residuals,vglm-method residuals.clm residuals.glm residuals.lrm residuals.ord residuals.orm residuals.PAsso residuals.polr
Summary of partial association analysissummary summary.PAsso
Surrogate responsesurrogate
Hypothesis testing of the partial association coefficientstest