Control of type 1 error in a hybrid complete two‐period vaccine efficacy trial. (16th October 2014)

• Record Type: Journal Article
• Authors: Dunning, Andrew J.; Reeves, John
• Is Part Of: Pharmaceutical statistics. Volume 13:Number 6(2014:Nov./Dec.)
• Page Start: 397
• Page End: 402
• Publication Date: 2014-10-16
• Subjects: Pharmacy -- Statistical methods -- Periodicals; Pharmacy -- Statistics -- Periodicals; 615.10727
• DOI: 10.1002/pst.1649
• Languages: English
• ISSNs: 1539-1604

Abstract

<abstract abstract-type="main" id="pst1649-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="pst1649-para-0001">A complete two‐period experimental design has been defined as one in which subjects are randomized to treatment, observed for the occurrence of an event of interest, re‐randomized, and observed again for the event in a second period. A 4‐year vaccine efficacy trial was planned to compare a high‐dose vaccine with a standard dose vaccine. Subjects would be randomized each year, and subjects who had participated in a previous year would be allowed to re‐enroll in a subsequent year and would be re‐randomized. A question of interest is whether positive correlation between observations on subjects who re‐enrolled would inflate the variance of test statistics. The effect of re‐enrollment and correlation on type 1 error in a 4‐year trial is investigated by simulation. As conducted, the trial met its power requirements after two years. Subjects therefore included some who participated for a single year and others who participated in both years. Those who participated in both years constituted a complete two‐period design. An algebraic expression for the variance of the treatment difference in a complete two‐period design is derived. It is shown that under a 'no difference' null, correlation does not result in variance inflation in this design. When there is a treatment difference, there is variance inflation but it is small. In the vaccine efficacy trial, the effect of correlation on the statistical inference was negligible. Copyright © 2014 John Wiley & Sons, Ltd.</p> </abstract>