estimate_semipmetric_erf: Estimate Semi-exposure-response Function (semi-ERF).

In wxwx1993/GPSmatching: Matching on Generalized Propensity Scores with Continuous Exposures

Estimate Semi-exposure-response Function (semi-ERF).

Description

Estimates the smoothed exposure-response function using a generalized additive model with splines.

Usage

estimate_semipmetric_erf(formula, family, data, ci_appr)

Arguments

formula	a vector of outcome variable in matched set.
family	a description of the error distribution (see ?gam).
data	dataset that formula is build upon.
ci_appr	causal inference approach (matching or weighting).

Details

This approach uses Generalized Additive Model (gam) using mgcv package.

Value

returns an object of class gam

Examples

m_d <- generate_syn_data(sample_size = 100)
pseudo_pop <- generate_pseudo_pop(m_d$Y,
                                  m_d$treat,
                                  m_d[c("cf1","cf2","cf3","cf4","cf5","cf6")],
                                  ci_appr = "matching",
                                  pred_model = "sl",
                                  sl_lib = c("m_xgboost"),
                                  params = list(xgb_nrounds=c(10,20,30),
                                   xgb_eta=c(0.1,0.2,0.3)),
                                  nthread = 1,
                                  covar_bl_method = "absolute",
                                  covar_bl_trs = 0.1,
                                  covar_bl_trs_type = "mean",
                                  max_attempt = 1,
                                  matching_fun = "matching_l1",
                                  delta_n = 1,
                                  scale = 0.5)

outcome_m <- estimate_semipmetric_erf (formula = Y ~ w,
                                       family = gaussian,
                                       data = pseudo_pop$pseudo_pop,
                                       ci_appr = "matching")

wxwx1993/GPSmatching documentation built on March 1, 2023, 9:32 p.m.