estimate_pmetric_erf: Estimate Parametric Exposure Response Function

View source: R/estimate_pmetric_erf.R

estimate_pmetric_erfR Documentation

Estimate Parametric Exposure Response Function

Description

Estimate a constant effect size for matched and weighted data set using parametric models

Usage

estimate_pmetric_erf(formula, family, data, ...)

Arguments

formula

a vector of outcome variable in matched set.

family

a description of the error distribution (see ?gnm)

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 gnm model.

Details

This method uses generalized nonlinear model (gnm) from gnm package.

Value

returns an object of class gnm

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_pmetric_erf(formula = Y ~ w,
                                  family = gaussian,
                                  data = data)


CausalGPS documentation built on Sept. 30, 2023, 1:06 a.m.