estimate_semipmetric_erf {CausalGPS}

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, ...)

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 Note that there should be a counter_weight column in this data.).

...

Additional parameters for further fine tuning the gam model.

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[, c("id", "w")],
                                  m_d[, c("id", "cf1","cf2","cf3",
                                          "cf4","cf5","cf6")],
                                  ci_appr = "matching",
                                  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,
                                  dist_measure = "l1",
                                  delta_n = 1,
                                  scale = 0.5)
data <- merge(m_d[, c("id", "Y")], pseudo_pop$pseudo_pop, by = "id")
outcome_m <- estimate_semipmetric_erf (formula = Y ~ w,
                                       family = gaussian,
                                       data = data)