Package: cdgd 0.3.5

cdgd: Causal Decomposition of Group Disparities

The framework of causal decomposition of group disparities developed by Yu and Elwert (2023) <doi:10.48550/arXiv.2306.16591>. This package implements the decomposition estimators that are based on efficient influence functions. For the nuisance functions of the estimators, both parametric and nonparametric options are provided, as well as manual options in case the default models are not satisfying.

Authors:Ang Yu [aut, cre, cph]

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cdgd.pdf |cdgd.html
cdgd/json (API)
NEWS

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

Bug tracker:https://github.com/ang-yu/cdgd/issues

Datasets:

On CRAN:

Conda:

3.00 score 1 stars 3 scripts 242 downloads 6 exports 76 dependencies

Last updated 8 months agofrom:5be1bf7abb. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 30 2025
R-4.5-winOKMar 30 2025
R-4.5-macOKMar 30 2025
R-4.5-linuxOKMar 30 2025
R-4.4-winOKMar 30 2025
R-4.4-macOKMar 30 2025
R-4.4-linuxOKMar 30 2025
R-4.3-winOKMar 30 2025
R-4.3-macOKMar 30 2025

Exports:cdgd0_manualcdgd0_mlcdgd0_pacdgd1_manualcdgd1_mlcdgd1_pa

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr