Multi-center clinical trials: Randomization and ancillary statistics

TL;DR

This paper develops design-based analysis methods for multi-center randomized clinical trials that rely solely on the randomization process, enhancing power especially when center variation exists.

Contribution

It introduces new analysis techniques based on the randomization design, allowing incorporation of centers and trial features without relying on model assumptions.

Findings

Significant increase in power with center variation.

Methods extend to group sequential trials.

Power improvements demonstrated through investigation.

Abstract

The purpose of this paper is to investigate and develop methods for analysis of multi-center randomized clinical trials which only rely on the randomization process as a basis of inference. Our motivation is prompted by the fact that most current statistical procedures used in the analysis of randomized multi-center studies are model based. The randomization feature of the trials is usually ignored. An important characteristic of model based analysis is that it is straightforward to model covariates. Nevertheless, in nearly all model based analyses, the effects due to different centers and, in general, the design of the clinical trials are ignored. An alternative to a model based analysis is to have analyses guided by the design of the trial. Our development of design based methods allows the incorporation of centers as well as other features of the trial design. The methods make use of conditioning on the ancillary statistics in the sample space generated by the randomization process. We have investigated the power of the methods and have found that, in the presence of center variation, there is a significant increase in power. The methods have been extended to group sequential trials with similar increases in power.