Sample size calculation based on efficient unconditional tests for clinical trials with historical controls

Guogen Shan; Sheniz Moonie; Jay Shen

doi:10.1080/10543406.2014.1000545

Sample size calculation based on efficient unconditional tests for clinical trials with historical controls

J Biopharm Stat. 2016;26(2):240-9. doi: 10.1080/10543406.2014.1000545. Epub 2014 Dec 31.

Authors

Guogen Shan¹, Sheniz Moonie¹, Jay Shen²

Affiliations

¹ a Department of Environmental and Occupational Health, Epidemiology and Biostatistics Program, School of Community Health Sciences , University of Nevada Las Vegas , Las Vegas , Nevada , USA.
² b Department of Health Care Administration and Policy, School of Community Health Sciences , University of Nevada Las Vegas , Las Vegas , Nevada , USA.

PMID: 25551261
DOI: 10.1080/10543406.2014.1000545

Abstract

In historical clinical trials, the sample size and the number of success in the control group are often considered as given. The traditional method for sample size calculation is based on an asymptotic approach developed by Makuch and Simon (1980). Exact unconditional approaches may be considered as alternative to control for the type I error rate where the asymptotic approach may fail to do so. We provide the sample size calculation using an efficient exact unconditional testing procedure based on estimation and maximization. The sample size using the exact unconditional approach based on estimation and maximization is generally smaller than those based on the other approaches.

Keywords: E+M approach; Exact test; historical clinical trial; sample size; unconditional test.

MeSH terms

Algorithms
Confidence Intervals
Controlled Clinical Trials as Topic / methods
Controlled Clinical Trials as Topic / statistics & numerical data*
Data Interpretation, Statistical
Historically Controlled Study / methods
Historically Controlled Study / statistics & numerical data*
Humans
Models, Statistical*
Sample Size*
Treatment Outcome