data_continuous

This is a simulated data example with three continuous endpoints.

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

data_continuous function

A data frame with 250 observations on the following 4 variables.<dl>
 <dt><code>id</code></dt>
<dd>A vector for the patient id.</dd> <dt><code>arm</code></dt>
<dd>A vector for the treatment groups.</dd> <dt><code>Y_1</code></dt>
<dd>A vector for the outcome of the first endpoint.</dd> <dt><code>Y_2</code></dt>
<dd>A vector for the outcome of the second endpoint.</dd> <dt><code>Y_3</code></dt>
<dd>A vector for the outcome of the third endpoint.</dd> 
</dl>

Format

An example with three continuous endpoints. — data_continuous

A data frame with 250 observations on the following 4 variables.<dl>
 <dt><code>id</code></dt>
<dd>A vector for the patient id.</dd>

 <dt><code>arm</code></dt>
<dd>A vector for the treatment groups.</dd>

 <dt><code>Y_1</code></dt>
<dd>A vector for the outcome of the first endpoint.</dd>

 <dt><code>Y_2</code></dt>
<dd>A vector for the outcome of the second endpoint.</dd>

 <dt><code>Y_3</code></dt>
<dd>A vector for the outcome of the third endpoint.</dd>

 
</dl>

data_continuous: An example with three continuous endpoints.

Description

Usage

Arguments

Format

Examples