visa_SimuData

An Example of Simulated Data for visa

datasets

Valid Improved Sparsity A-Learning (VISA) provides a new method for selecting important variables involved in optimal treatment regime from a multiply robust perspective. The VISA estimator achieves its success by borrowing the strengths of both model averaging (ARM, Yuhong Yang, 2001) <doi:10.1198/016214501753168262> and variable selection (PAL, Chengchun Shi, Ailin Fan, Rui Song and Wenbin Lu, 2018) <doi:10.1214/17-AOS1570>. The package is an implementation of Zishu Zhan and Jingxiao Zhang. (2022+).

Zishu Zhan

visaOTR

Valid Improved Sparsity A-Learning for Optimal Treatment
Decision

Jingxiao Zhang

visa_SimuData function

The dataset visa_SimuData contains n = 50 samples with p = 10 covariates and treatment variable<dl>
<dt>y</dt>
<dd>the response</dd><dt>x</dt>
<dd>the covariates</dd><dt>a</dt>
<dd>the treatment received</dd>
</dl>

Format

visa_SimuData — visa_SimuData

The dataset visa_SimuData contains n = 50 samples with p = 10 covariates and treatment variable<dl>
<dt>y</dt>
<dd>the response</dd>

<dt>x</dt>
<dd>the covariates</dd>

<dt>a</dt>
<dd>the treatment received</dd>


</dl>

visa_SimuData: visa_SimuData

Description

Usage

Arguments

Format