Comparisons of minimization and Atkinson's algorithm

Senn, S., Anisimov, V. and Fedorov, V. (2010) Comparisons of minimization and Atkinson's algorithm. Statistics in Medicine, 29(7-8), pp. 721-730. (doi: 10.1002/sim.3763)

Abstract

Some general points regarding efficiency in clinical trials are made. Reasons as to why fitting many covariates to adjust the estimate of the treatment effect may be less problematic than commonly supposed are given. Two methods of dynamic allocation of patients based on covariates, minimization and Atkinson's approach, are compared and contrasted for the particular case where all covariates are binary. The results of Monte Carlo simulations are also presented. It is concluded that in the cases considered, Atkinson's approach is slightly more efficient than minimization although the difference is unlikely to be very important in practice. Both are more efficient than simple randomization, although it is concluded that fitting covariates may make a more valuable and instructive contribution to inferences about treatment effects than only balancing them.

• Item Type: Articles
• Keywords: Randomization, clinical trials, optimal design, covariates, dynamic allocation
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Anisimov, Dr Vladimir and Senn, Professor Stephen
• Authors: Senn, S., Anisimov, V., and Fedorov, V.
• Subjects: H Social Sciences > HA Statistics
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Statistics in Medicine
• Journal Abbr.: Stat Med
• ISSN: 0277-6715
• ISSN (Online): 1097-0258
• Published Online: 08 March 2010

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
46555	1	Minimisation and randomisation in clinical trials	Stephen Senn	GlaxoSmithKline (GLAXO-SK)	UNSPECIFIED	M&S - STATISTICS