psdata_bin_prospective_sp: Prospective Superpopulation Dataset for PSweight Analysis

In PSweight: Propensity Score Weighting for Causal Inference with Observational Studies and Randomized Trials

Prospective Superpopulation Dataset for PSweight Analysis

Description

A simulated dataset representing the prospective superpopulation (i.e. the full dataset) for propensity score weighting analysis under a prospective design. In this design, the sampling probability is determined solely by covariates.

Usage

data(psdata_bin_prospective_sp)

Format

A data frame with 1500 rows and 10 variables:

Y

Outcome variable.

trt

Binary treatment indicator (coded as 1 and 2).

cov1, cov2, cov3, cov4, cov5, cov6

Pre-treatment covariates.

sampling_prob

Sampling probability computed solely from covariates (e.g., using a logistic function).

survey_weight

Survey weight computed as the inverse of sampling_prob.

sample_indicator

Indicator variable (0/1) denoting whether an observation was selected into the sample.

Details

In the prospective design, sampling is conducted before treatment assignment, and the probability of an observation being selected depends only on its covariate values.

Examples

data(psdata_bin_prospective_sp)
head(psdata_bin_prospective_sp)

PSweight documentation built on April 3, 2025, 10:27 p.m.