Package: jointVIP 1.0.0

jointVIP: Prioritize Variables with Joint Variable Importance Plot in Observational Study Design

In the observational study design stage, matching/weighting methods are conducted. However, when many background variables are present, the decision as to which variables to prioritize for matching/weighting is not trivial. Thus, the joint treatment-outcome variable importance plots are created to guide variable selection. The joint variable importance plots enhance variable comparisons via unadjusted bias curves derived under the omitted variable bias framework. The plots translate variable importance into recommended values for tuning parameters in existing methods. Post-matching and/or weighting plots can also be used to visualize and assess the quality of the observational study design. The method motivation and derivation is presented in "Prioritizing Variables for Observational Study Design using the Joint Variable Importance Plot" by Liao et al. (2024) <doi:10.1080/00031305.2024.2303419>. See the package paper by Liao and Pimentel (2023) <arxiv:2302.10367> for a beginner friendly user introduction.

Authors:Lauren D. Liao [aut, cre], Samuel D. Pimentel [aut]

jointVIP_1.0.0.tar.gz
jointVIP_1.0.0.zip(r-4.7-any)jointVIP_1.0.0.zip(r-4.6-any)jointVIP_1.0.0.zip(r-4.5-any)
jointVIP_1.0.0.tgz(r-4.6-any)jointVIP_1.0.0.tgz(r-4.5-any)
jointVIP_1.0.0.tar.gz(r-4.7-any)jointVIP_1.0.0.tar.gz(r-4.6-any)
jointVIP_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
jointVIP/json (API)

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

Bug tracker:https://github.com/ldliao/jointvip/issues

Pkgdown/docs site:https://ldliao.github.io

Datasets:
  • brfss - 2015 Behavioral Risk Factor Surveillance System

On CRAN:

Conda:

causal-inferenceobservational-studystudy-design

5.44 score 7 stars 39 scripts 437 downloads 6 exports 19 dependencies

Last updated from:8d55fdfb31. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK229
source / vignettesOK240
linux-releaseOK184
macos-releaseOK189
macos-oldrelOK209
windows-develOK91
windows-releaseOK118
windows-oldrelOK101
wasm-releaseOK137

Exports:bootstrap.plotcreate_jointVIPcreate_post_jointVIPget_boot_measuresget_measuresget_post_measures

Dependencies:clicpp11farverggplot2ggrepelgluegtableisobandlabelinglifecycleR6RColorBrewerRcpprlangS7scalesvctrsviridisLitewithr

Additional options available in the jointVIP package
Setting up to demonstrate jointVIP | Demonstration for additional options in summary() and print() | Demonstration for additional options in plot() | Post-analysis parameters examples
Rendered fromadditional_options.Rmdusingknitr::rmarkdown

Last update: 2024-07-04
Started: 2022-12-20

Get started with jointVIP
The purpose of the jointVIP | Set up for example | Data cleaning | Specifying parameters for the create_jointVIP() function | Diagnostics with a jointVIP object | Matching examples | Optimal pair matching | Optimal weighting | Post-matching/weighting assessment with post_jointVIP object | References
Rendered fromjointVIP.Rmdusingknitr::rmarkdown

Last update: 2023-03-08
Started: 2022-12-13