Other packages > Find by keyword >

jointVIP  

Prioritize Variables with Joint Variable Importance Plot in Observational Study Design
View on CRAN: Click here


Download and install jointVIP package within the R console
Install from CRAN:
install.packages("jointVIP")

Install from Github:
library("remotes")
install_github("cran/jointVIP")

Install by package version:
library("remotes")
install_version("jointVIP", "1.0.1")



Attach the package and use:
library("jointVIP")
Maintained by
Lauren D. Liao
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-21
Latest Update: 2024-11-22
Description:
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 "Using Joint Variable Importance Plots to Prioritize Variables in Assessing the Impact of Glyburide on Adverse Birth Outcomes" by Liao et al. (2023) . See the package paper by Liao and Pimentel (2023) for a beginner friendly user introduction.
How to cite:
Lauren D. Liao (2022). jointVIP: Prioritize Variables with Joint Variable Importance Plot in Observational Study Design. R package version 1.0.1, https://cran.r-project.org/web/packages/jointVIP. Accessed 26 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:50), 0.1.0 (2022-12-21 13:20), 0.1.1 (2023-01-26 10:30), 0.1.2 (2023-03-08 23:00), 1.0.0 (2024-11-22 04:10)
Other packages that cited jointVIP R package
View jointVIP citation profile
Other R packages that jointVIP depends, imports, suggests or enhances
Complete documentation for jointVIP
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

ncodeR  
Techniques for Automated Classifiers
A set of techniques that can be used to develop, validate, and implement automated classifiers. A po ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
clinUtils  
General Utility Functions for Analysis of Clinical Data
Utility functions to facilitate the import, the reporting and analysis of clinical data. Example ...
Download / Learn more Package Citations See dependency  
PCADSC  
Tools for Principal Component Analysis-Based Data Structure Comparisons
A suite of non-parametric, visual tools for assessing differences in data structures for two datase ...
Download / Learn more Package Citations See dependency  
SelvarMix  
Regularization for Variable Selection in Model-Based Clustering and Discriminant Analysis
Performs a regularization approach to variable selection in themodel-based clustering and classifica ...
Download / Learn more Package Citations See dependency  
RCytoGPS  
Using Cytogenetics Data in R
Defines classes and methods to process text-based cytogenetics using the CytoGPS web site, then imp ...
Download / Learn more Package Citations See dependency  

28,332

R Packages

239,283

Dependencies

75,113

Author Associations

28,333

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA