covariate

Covariate table for implement of CARM randomization.

datasets

In randomized controlled trial (RCT), balancing covariate is often one of the most important concern. CARM package provides functions to balance the covariates and generate allocation sequence by covariate-adjusted Adaptive Randomization via Mahalanobis-distance (ARM) for RCT. About what ARM is and how it works please see Y. Qin, Y. Li, W. Ma, H. Yang, and F. Hu (2024). "Adaptive randomization via Mahalanobis distance" Statistica Sinica. <doi:10.5705/ss.202020.0440>. In addition, the package is also suitable for the randomization process of multi-arm trials. For details, please see Yang H, Qin Y, Wang F, et al. (2023). "Balancing covariates in multi-arm trials via adaptive randomization" Computational Statistics & Data Analysis.<doi:10.1016/j.csda.2022.107642>.

Fanglu Chen

CARM

Covariate-Adjusted Adaptive Randomization via
Mahalanobis-Distance

Haoyu Yang

Yichen Qin

Yang Li

covariate function

A data frame with N rows and P columns:<dl>
<dt>center</dt>
<dd>the hospital of trial implement</dd><dt>male</dt>
<dd>1 = male, 0 = female</dd><dt>age</dt>
<dd>age</dd><dt>X_6MWD1</dt>
<dd>Baseline 6-minute walk distance, 6MWD</dd><dt>SF12_PCS1</dt>
<dd>Baseline SF-12 Physical Health Component Scores (PCS-12)</dd></dl>

Format

Example dataset: covariate — covariate

A data frame with N rows and P columns:<dl>
<dt>center</dt>
<dd>the hospital of trial implement</dd>

<dt>male</dt>
<dd>1 = male, 0 = female</dd>

<dt>age</dt>
<dd>age</dd>

<dt>X_6MWD1</dt>
<dd>Baseline 6-minute walk distance, 6MWD</dd>

<dt>SF12_PCS1</dt>
<dd>Baseline SF-12 Physical Health Component Scores (PCS-12)</dd>



</dl>

covariate: Example dataset: covariate

Description

Usage

Arguments

Format

Examples