Package: WeightIt 1.3.2
WeightIt: Weighting for Covariate Balance in Observational Studies
Generates balancing weights for causal effect estimation in observational studies with binary, multi-category, or continuous point or longitudinal treatments by easing and extending the functionality of several R packages and providing in-house estimation methods. Available methods include those that rely on parametric modeling, optimization, and machine learning. Also allows for assessment of weights and checking of covariate balance by interfacing directly with the 'cobalt' package. Methods for estimating weighted regression models that take into account uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how to install any package 'WeightIt' uses, including those that may not be on CRAN.
Authors:
WeightIt_1.3.2.tar.gz
WeightIt_1.3.2.zip(r-4.5)WeightIt_1.3.2.zip(r-4.4)WeightIt_1.3.2.zip(r-4.3)
WeightIt_1.3.2.tgz(r-4.4-any)WeightIt_1.3.2.tgz(r-4.3-any)
WeightIt_1.3.2.tar.gz(r-4.5-noble)WeightIt_1.3.2.tar.gz(r-4.4-noble)
WeightIt_1.3.2.tgz(r-4.4-emscripten)WeightIt_1.3.2.tgz(r-4.3-emscripten)
WeightIt.pdf |WeightIt.html✨
WeightIt/json (API)
NEWS
# Install 'WeightIt' in R: |
install.packages('WeightIt', repos = c('https://ngreifer.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ngreifer/weightit/issues
- msmdata - Simulated data for a 3 time point sequential study
causal-inferenceinverse-probability-weightsobservational-studypropensity-scores
Last updated 2 days agofrom:72b611f054. Checks:OK: 5 ERROR: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-win | OK | Nov 04 2024 |
R-4.5-linux | OK | Nov 04 2024 |
R-4.4-win | OK | Nov 04 2024 |
R-4.4-mac | ERROR | Nov 04 2024 |
R-4.3-win | OK | Nov 04 2024 |
R-4.3-mac | ERROR | Nov 04 2024 |
Exports:.weightit_methodsas.weightitas.weightitMSMcalibratecoxph_weightitESSget_w_from_psglm_weightitlm_weightitmake_full_rankmultinom_weightitordinal_weightitsbpstrimweightitweightit.fitweightitMSM
Dependencies:backportschkclicobaltcolorspacecrayonfansifarvergenericsggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
Estimating Effects After Weighting
Rendered fromestimating-effects.Rmd
usingknitr::rmarkdown_notangle
on Nov 04 2024.Last update: 2024-10-03
Started: 2023-04-10
Installing Supporting Packages
Rendered frominstalling-packages.Rmd
usingknitr::rmarkdown_notangle
on Nov 04 2024.Last update: 2024-10-03
Started: 2022-06-22
Using WeightIt to Estimate Balancing Weights
Rendered fromWeightIt.Rmd
usingknitr::rmarkdown_notangle
on Nov 04 2024.Last update: 2024-08-10
Started: 2020-08-20