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mvGPS  

Causal Inference using Multivariate Generalized Propensity Score
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mvGPS", "1.2.2")



Attach the package and use:
library("mvGPS")
Maintained by
Justin Williams
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-17
Latest Update: 2021-12-07
Description:
Methods for estimating and utilizing the multivariate generalized propensity score (mvGPS) for multiple continuous exposures described in Williams, J.R, and Crespi, C.M. (2020) . The methods allow estimation of a dose-response surface relating the joint distribution of multiple continuous exposure variables to an outcome. Weights are constructed assuming a multivariate normal density for the marginal and conditional distribution of exposures given a set of confounders. Confounders can be different for different exposure variables. The weights are designed to achieve balance across all exposure dimensions and can be used to estimate dose-response surfaces.
How to cite:
Justin Williams (2020). mvGPS: Causal Inference using Multivariate Generalized Propensity Score. R package version 1.2.2, https://cran.r-project.org/web/packages/mvGPS. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0.2 (2020-09-17 11:10), 1.1.1 (2021-04-28 14:30), 1.2.1 (2021-10-17 01:30)
Other packages that cited mvGPS R package
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Other R packages that mvGPS depends, imports, suggests or enhances
Complete documentation for mvGPS
Functions, R codes and Examples using the mvGPS R package
Some associated functions: D_C_check . X_check . bal . gen_D . hull_sample . mvGPS . 
Some associated R codes: bal.R . gen_D.R . hull_sample.R . mvGPS.R .  Full mvGPS package functions and examples
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