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Implications of Clinical Trial Design on Sample Size Requirements
Author(s) -
Andrew C. Leon
Publication year - 2007
Publication title -
schizophrenia bulletin
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.823
H-Index - 190
eISSN - 1745-1701
pISSN - 0586-7614
DOI - 10.1093/schbul/sbn035
Subject(s) - randomized controlled trial , sample size determination , type i and type ii errors , statistical power , randomized experiment , research design , computer science , treatment and control groups , neurocognitive , statistics , reliability engineering , medicine , cognition , mathematics , engineering , psychiatry , surgery
The primary goal in designing a randomized controlled clinical trial (RCT) is to minimize bias in the estimate of treatment effect. Randomized group assignment, double-blinded assessments, and control or comparison groups reduce the risk of bias. The design must also provide sufficient statistical power to detect a clinically meaningful treatment effect and maintain a nominal level of type I error. An attempt to integrate neurocognitive science into an RCT poses additional challenges. Two particularly relevant aspects of such a design often receive insufficient attention in an RCT. Multiple outcomes inflate type I error, and an unreliable assessment process introduces bias and reduces statistical power. Here we describe how both unreliability and multiple outcomes can increase the study costs and duration and reduce the feasibility of the study. The objective of this article is to consider strategies that overcome the problems of unreliability and multiplicity.

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