estimate_gps {CausalGPS} | R Documentation |
Estimate generalized propensity score (GPS) values
Description
Estimates GPS value for each observation using normal or kernel approaches.
Usage
estimate_gps(
w,
c,
gps_density = "normal",
params = list(),
sl_lib = c("m_xgboost"),
nthread = 1,
...
)
Arguments
w |
A data frame of observed continuous exposure variable. Including
|
c |
A data frame of observed covariates variable. Also includes |
gps_density |
Model type which is used for estimating GPS value,
including |
params |
Includes list of parameters that are used internally. Unrelated parameters will be ignored. |
sl_lib |
A vector of prediction algorithms. |
nthread |
An integer value that represents the number threads to be used in a shared memory system. |
... |
Additional arguments passed to the model. |
Value
The function returns a S3 object. Including the following:
-
dataset
:id
,w
,gps
e_gps_pred
e_gps_std_pred
w_resid
gps_mx (min and max of gps)
w_mx (min and max of w).
used_params
Note
If internal.use
is set to be FALSE, only original data set + GPS will
be returned.
The outcome variable is not used in estimating the GPS value. However, it is used in compiling the data set with GPS values.
Examples
m_d <- generate_syn_data(sample_size = 100)
data_with_gps <- estimate_gps(m_d[, c("id", "w")],
m_d[, c("id", "cf1", "cf2", "cf3",
"cf4", "cf5", "cf6")],
gps_density = "normal",
params = list(xgb_max_depth = c(3,4,5),
xgb_nrounds=c(10,20,30,40,50,60)),
nthread = 1,
sl_lib = c("m_xgboost")
)