pats

a dataframe. Each row contains an individual's covariate profile and each column corresponds to a covariate. It contains the following columns<dl class="dl-horizontal">
 <dt>gender</dt><dd>Options are <code>male</code> and <code>female</code>.</dd>
 <dt>employment status</dt><dd>Options are "unemployment" (<code>unemp</code>), "part time" (<code>part.</code>), "full time" (<code>full.</code>).</dd>
 <dt>income</dt><dd>Options are <code>&gt;= 1w</code>, <code>&lt;= 0.5w</code>, <code>0.5~1w</code>.</dd>
 <dt>marriage status</dt><dd>Options are <code>unmarried</code>, <code>married</code>, <code>divorced</code></dd>
 </dl>

gives the simulated covariate profile of patients for clincal trials.

datasets

Provides functions and command-line user interface to generate allocation sequence by covariate-adaptive randomization for clinical trials. The package currently supports six covariate-adaptive randomization procedures. Three hypothesis testing methods that are valid and robust under covariate-adaptive randomization are also available in the package to facilitate the inference for treatment effect under the included randomization procedures. Additionally, the package provides comprehensive and efficient tools to allow one to evaluate and compare the performance of randomization procedures and tests based on various criteria.

Xiaoqing Ye

carat

Covariate-Adaptive Randomization for Clinical Trials

Fuyi Tu

Wei Ma

Feifang Hu

pats function

a dataframe. Each row contains an individual's covariate profile and each column corresponds to a covariate. It contains the following columns<dl class='dl-horizontal'>
 <dt>gender</dt><dd>Options are <code>male</code> and <code>female</code>.</dd>
 <dt>employment status</dt><dd>Options are "unemployment" (<code>unemp</code>), "part time" (<code>part.</code>), "full time" (<code>full.</code>).</dd>
 <dt>income</dt><dd>Options are <code>&gt;= 1w</code>, <code>&lt;= 0.5w</code>, <code>0.5~1w</code>.</dd>
 <dt>marriage status</dt><dd>Options are <code>unmarried</code>, <code>married</code>, <code>divorced</code></dd>
 </dl>

pats: Data of Covariate Profile of Patients

Description

Usage

Arguments