estimate_gps {GPCERF} | R Documentation |
Estimates a model for generalized propensity score (GPS) using parametric approach.
estimate_gps(cov_mt, w_all, sl_lib, dnorm_log)
cov_mt |
A covariate matrix containing all covariates. Each row is a data sample and each column is a covariate. |
w_all |
A vector of observed exposure levels. |
sl_lib |
A vector of SuperLearner's package libraries. |
dnorm_log |
Logical, if TRUE, probabilities p are given as log(p). |
A data.frame that includes:
a vector of estimated GPS at the observed exposure levels;
a vector of estimated conditional means of exposure levels when the covariates are fixed at the observed values;
estimated standard deviation of exposure levels
a vector of observed exposure levels.
data <- generate_synthetic_data(sample_size = 200)
gps_m <- estimate_gps(cov_mt = data[,-(1:2)],
w_all = data$treat,
sl_lib = c("SL.xgboost"),
dnorm_log = FALSE)