psdata_bin_prospective_sp

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.

datasets

Supports propensity score weighting analysis of observational studies and randomized trials. Enables the estimation and inference of average causal effects with binary and multiple treatments using overlap weights (ATO), inverse probability of treatment weights (ATE), average treatment effect among the treated weights (ATT), matching weights (ATM) and entropy weights (ATEN), with and without propensity score trimming. These weights are members of the family of balancing weights introduced in Li, Morgan and Zaslavsky (2018) <doi:10.1080/01621459.2016.1260466> and Li and Li (2019) <doi:10.1214/19-AOAS1282>.

Yukang Zeng

PSweight

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

Tianhui Zhou

Guangyu Tong

Fan Li

Laine Thomas

psdata_bin_prospective_sp function

A data frame with 1500 rows and 10 variables:<dl>
 <dt>Y</dt>
<dd>Outcome variable.</dd> <dt>trt</dt>
<dd>Binary treatment indicator (coded as 1 and 2).</dd> <dt>cov1, cov2, cov3, cov4, cov5, cov6</dt>
<dd>Pre-treatment covariates.</dd> <dt>sampling_prob</dt>
<dd>Sampling probability computed solely from covariates (e.g., using a logistic function).</dd> <dt>survey_weight</dt>
<dd>Survey weight computed as the inverse of <code>sampling_prob</code>.</dd> <dt>sample_indicator</dt>
<dd>Indicator variable (0/1) denoting whether an observation was selected into the sample.</dd>
</dl>

Format

Prospective Superpopulation Dataset for PSweight Analysis — psdata_bin_prospective_sp

A data frame with 1500 rows and 10 variables:<dl>
 <dt>Y</dt>
<dd>Outcome variable.</dd>

 <dt>trt</dt>
<dd>Binary treatment indicator (coded as 1 and 2).</dd>

 <dt>cov1, cov2, cov3, cov4, cov5, cov6</dt>
<dd>Pre-treatment covariates.</dd>

 <dt>sampling_prob</dt>
<dd>Sampling probability computed solely from covariates (e.g., using a logistic function).</dd>

 <dt>survey_weight</dt>
<dd>Survey weight computed as the inverse of <code>sampling_prob</code>.</dd>

 <dt>sample_indicator</dt>
<dd>Indicator variable (0/1) denoting whether an observation was selected into the sample.</dd>


</dl>

psdata_bin_prospective_sp: Prospective Superpopulation Dataset for PSweight Analysis

Description

Usage

Arguments

Format

Details

Examples