ADSL

A data frame with baseline characteristics for 1500 patients used to derive <code>KHCE</code> dataset.

datasets

Simulate and analyze hierarchical composite endpoints. Win odds is the main analysis method, but other win statistics (win ratio, net benefit) are also implemented, provided there is no censoring. See Gasparyan SB et al (2023) "Hierarchical Composite Endpoints in COVID-19: The DARE-19 Trial." Case Studies in Innovative Clinical Trials, 95-148. Chapman; Hall/CRC. <doi:10.1201/9781003288640-7>.

Samvel B. Gasparyan

Design and Analysis of Hierarchical Composite Endpoints

ADSL function

a data frame with 1500 rows and 4 variables:<dl>
<dt>ID</dt>
<dd>patient identifiers, numeric</dd><dt>TRTPN</dt>
<dd>treatment values, 1 Active or 2 Placebo, numeric</dd><dt>EGFRBL</dt>
<dd>Baseline GFR values of patients, numeric</dd><dt>STRATAN</dt>
<dd>strata 1-4, higher value means a higher risk for kidney disease progression, numeric</dd>
</dl>

Format

Baseline characteristics dataset of patients with kidney function assessments. — ADSL

a data frame with 1500 rows and 4 variables:<dl>
<dt>ID</dt>
<dd>patient identifiers, numeric</dd>

<dt>TRTPN</dt>
<dd>treatment values, 1 Active or 2 Placebo, numeric</dd>

<dt>EGFRBL</dt>
<dd>Baseline GFR values of patients, numeric</dd>

<dt>STRATAN</dt>
<dd>strata 1-4, higher value means a higher risk for kidney disease progression, numeric</dd>


</dl>

ADSL: Baseline characteristics dataset of patients with kidney function assessments.

Description

Usage

Arguments

Format

Examples