mvGPS: Causal Inference using Multivariate Generalized Propensity Score

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) <arxiv:2008.13767>. 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.

Package details

AuthorJustin Williams [aut, cre] (<https://orcid.org/0000-0002-5045-2764>)
MaintainerJustin Williams <williazo@ucla.edu>
LicenseMIT + file LICENSE
Version1.2.2
URL https://github.com/williazo/mvGPS
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mvGPS")

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mvGPS documentation built on Dec. 11, 2021, 9:06 a.m.