Package: jointCalib 0.1.2

Maciej Beręsewicz

jointCalib: A Joint Calibration of Totals and Quantiles

A small package containing functions to perform a joint calibration of totals and quantiles. The calibration for totals is based on Deville and Särndal (1992) <doi:10.1080/01621459.1992.10475217>, the calibration for quantiles is based on Harms and Duchesne (2006) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X20060019255>. The package uses standard calibration via the 'survey', 'sampling' or 'laeken' packages. In addition, entropy balancing via the 'ebal' package and empirical likelihood based on codes from Wu (2005) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2005002/article/9051-eng.pdf> can be used. See the paper by Beręsewicz and Szymkowiak (2023) for details <arxiv:2308.13281>. The package also includes functions to reweight the control group to the treatment reference distribution and to balance the covariate distribution using the covariate balancing propensity score via the 'CBPS' package for binary treatment observational studies.

Authors:Maciej Beręsewicz [aut, cre]

jointCalib_0.1.2.tar.gz
jointCalib_0.1.2.zip(r-4.7-any)jointCalib_0.1.2.zip(r-4.6-any)jointCalib_0.1.2.zip(r-4.5-any)
jointCalib_0.1.2.tgz(r-4.6-any)jointCalib_0.1.2.tgz(r-4.5-any)
jointCalib_0.1.2.tar.gz(r-4.7-any)jointCalib_0.1.2.tar.gz(r-4.6-any)
jointCalib_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
jointCalib/json (API)

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

Bug tracker:https://github.com/ncn-foreigners/jointcalib/issues

Pkgdown/docs site:https://ncn-foreigners.github.io

On CRAN:

Conda:

calibrationcausal-inferenceprobability-samplessamplingsurveysurvey-methodologyweighting

5.20 score 8 stars 8 scripts 178 downloads 6 exports 32 dependencies

Last updated from:0911e86272. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK153
source / vignettesOK199
linux-release-x86_64OK149
macos-release-arm64OK121
macos-oldrel-arm64OK115
windows-devel-x86_64OK111
windows-release-x86_64OK109
windows-oldrel-x86_64OK105
wasm-releaseOK113

Exports:calib_elcontrol_calibjoint_calibjoint_calib_attjoint_calib_cbpsjoint_calib_create_matrix

Dependencies:backportsbootCBPSchkclicodetoolsDBIebalforeachglmnetiteratorslaekenlatticelifecyclelpSolveMASSMatchItmathjaxrMatrixminqamitoolsnnetnumDerivRcppRcppArmadilloRcppEigenRcppProgressrlangsamplingshapesurveysurvival

Calibration of quantiles and a joint calibration of totals and quanitles for surveys
Setup | Examples | Basic example | Example 1 -- census case | Using jointCalib package | Using survey package
Rendered fromb_survey.Rmdusingknitr::rmarkdown

Last update: 2025-04-03
Started: 2023-10-11

Balancing distributions for observational studies
Theory | Distributional entropy balancing | Distributional propensity score method | Packages | ATT with entropy balancing and other methods | Single variable: age | More variables | More variables: all variables | ATT with CBPS and DPS [work in progress]
Rendered fromd_causal.Rmdusingknitr::rmarkdown

Last update: 2023-10-11
Started: 2023-10-11

Calibration and inverse probability weighting for non-probability samples
Rendered fromc_nonprob.Rmdusingknitr::rmarkdown

Last update: 2023-10-11
Started: 2023-10-11

Joint calibration estimators for totals and quantiles
Introduction | Calibration estimator for a total | Calibration estimator for a quantile | Joint calibration of totals and quantiles | References
Rendered froma_theory.Rmdusingknitr::rmarkdown

Last update: 2023-10-11
Started: 2023-10-11