codiacs

Primary data analysis for sequential multiple assignment randomization trial (SMART) and calibration tools for clinical trial planning purposes. \n
The methods used for this package include: \n
(1) Likelihood-based global test (hypothesis test, power calculation) by in Zhong X., Cheng, B., Qian M., Cheung Y.K. (2019) <doi: 10.1016/j.cct.2019.105830>. \n
(2) IPWE-based global test (hypotehsis test, power calculation) by Ogbagaber S.B., Karp J., Wahed A.S. (2016) <doi:10.1002/sim.6747>. \n
(3) G estimates (pairwise comparison, power calculation) by Lavori R., Dawson P.W. (2012) <doi: 10.1093/biostatistics/kxr016>. \n
(4) IPW estimates (pairwise comparison, power calculation) by Murphy S.A. (2005) <doi: 10.1002/sim.2022>. \n
(5) SAMRT with adaptive randomization by Cheung Y.K. (2015) <doi: 10.1111/biom.12258>.

Tony Zhong

SMARTAR

Sequential Multiple Assignment Randomized Trial and Adaptive
Randomization

codiacs function

A dataset with 108 row and 6 variables:<dl class="dl-horizontal">
<dt>ID</dt><dd>Patient ID</dd>
<dt>A1</dt><dd>Stage-1 treatment</dd>
<dt>O2</dt><dd>Intermediate response</dd>
<dt>A2</dt><dd>Stage-2 treatment</dd>
<dt>Y</dt><dd>Final primary outcome</dd>
<dt>grou</dt><dd>Treatment sequence</dd>
</dl>

Format

Example data collected from CODIACS trial — codiacs

A dataset with 108 row and 6 variables:<dl class='dl-horizontal'>
<dt>ID</dt><dd>Patient ID</dd>
<dt>A1</dt><dd>Stage-1 treatment</dd>
<dt>O2</dt><dd>Intermediate response</dd>
<dt>A2</dt><dd>Stage-2 treatment</dd>
<dt>Y</dt><dd>Final primary outcome</dd>
<dt>grou</dt><dd>Treatment sequence</dd>
</dl>

codiacs: Example data collected from CODIACS trial

Description

Usage

Arguments

Format