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) . 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.


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install.packages("mvGPS")

1.1.1 by Justin Williams, 3 months ago


https://github.com/williazo/mvGPS


Report a bug at https://github.com/williazo/mvGPS/issues


Browse source code at https://github.com/cran/mvGPS


Authors: Justin Williams [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rdpack, MASS, WeightIt, cobalt, matrixNormal, geometry, sp, gbm, CBPS

Suggests testthat, knitr, dagitty, ggdag, dplyr, rmarkdown


See at CRAN