Z_t_trt

This is a simulated data example for the covariate history in the treatment group.

datasets

Calculate the win statistics (win ratio, net benefit and win odds) for prioritized multiple endpoints, plot the win statistics and win proportions over study time if at least one time-to-event endpoint is analyzed, and simulate datasets with dependent endpoints. The package can handle any type of outcomes (continuous, ordinal, binary, time-to-event) and allow users to perform stratified analysis, inverse probability of censoring weighting (IPCW) and inverse probability of treatment weighting (IPTW) analysis.

Ying Cui

WINS

The R WINS Package

Bo Huang

Z_t_trt function

A data frame with 796 observations on the following 4 variables.<dl>
 <dt><code>id</code></dt>
<dd>A vector for the patient id.</dd> <dt><code>time</code></dt>
<dd>A vector for the observed time of the covariate.</dd> <dt><code>Z1</code></dt>
<dd>A vector for the observed value of the first covariate.</dd> <dt><code>Z2</code></dt>
<dd>A vector for the observed value of the second covariate.</dd> 
</dl>

Format

Covariate history in the treatment group. — Z_t_trt

A data frame with 796 observations on the following 4 variables.<dl>
 <dt><code>id</code></dt>
<dd>A vector for the patient id.</dd>

 <dt><code>time</code></dt>
<dd>A vector for the observed time of the covariate.</dd>

 <dt><code>Z1</code></dt>
<dd>A vector for the observed value of the first covariate.</dd>

 <dt><code>Z2</code></dt>
<dd>A vector for the observed value of the second covariate.</dd>

 
</dl>

Z_t_trt: Covariate history in the treatment group.

Description

Usage

Arguments

Format

Examples