TTE_pipeline: Target Trial Emulation (TTE) Pipeline

In debiasedTrialEmulation: Pipeline for Debiased Target Trial Emulation

Target Trial Emulation (TTE) Pipeline

Description

Implements a Target Trial Emulation pipeline using propensity score methods, including matching, weighting, and stratification.

Usage

TTE_pipeline(data, xvars, yvars, ncovars = NULL, ps_type, outcome_measure)

Arguments

data	A dataset containing treatment assignment, covariates, and outcomes.
xvars	A character vector of covariate names used for propensity score estimation.
yvars	A character vector of primary outcome variable names.
ncovars	Optional. A character vector of negative control outcome variable names.
ps_type	The propensity score method: "Matching", "Stratification", or "Weighting".
outcome_measure	The outcome measure to estimate: "RR" (Risk Ratio), "OR" (Odds Ratio), or "HR" (Hazard Ratio).

Value

An object of class "TTE" containing the propensity score analysis results

Examples

library("dplyr")
data(demo_data)
xvars <- c("eth_cat", "age_cat", "sex", "cohort_entry_month",
           "obese", "pmca_index", "n_ed", "n_inpatient",
           "n_tests", "imm_date_diff_grp", "medical_1",
           "medical_2", "medical_3", "medical_4", "medical_5")
yvars1 <- colnames(demo_data %>% select(starts_with("visits_")))
yvars2 <- colnames(demo_data %>% select(starts_with("event_")))
# without negative controls
TTE_pipeline(demo_data, xvars=xvars, yvars=yvars1,
            ps_type="Matching", outcome_measure="RR")
# with negative controls
ncovars1 <- colnames(demo_data %>% select(starts_with("nco_visits_")))
TTE_pipeline(demo_data, xvars=xvars, yvars=yvars1,
             ncovars=ncovars1, ps_type="Matching", outcome_measure="RR")

debiasedTrialEmulation documentation built on March 20, 2026, 1:07 a.m.