Sample Size

Lawrence M. Friedman (), Curt D. Furberg () and David L. DeMets ()
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Curt D. Furberg: Wake Forest University, School of Medicine
David L. DeMets: University of Wisconsin, Department of Biostatistics & Medical Informatics

Chapter Chapter 8 in Fundamentals of Clinical Trials, 2010, pp 133-167 from Springer

Abstract: Abstract The size of the study should be considered early in the planning phase. In some instances, no formal sample size is ever calculated. Instead, the number of participants available to the investigators during some period of time determines the size of the study. Many clinical trials that do not carefully consider the sample size requirements turn out to lack the statistical power or ability to detect intervention effects of a magnitude that has clinical importance. In 1978, Freiman and colleagues [1] reviewed the power of 71 published randomized controlled clinical trials, which failed to find significant differences between groups. “Sixty-seven of the trials had a greater than 10% risk of missing a true 25% therapeutic improvement, and with the same risk, 50 of the trials could have missed a 50% improvement.” In other instances, the sample size estimation may assume an unrealistically large intervention effect. Thus, the power for more realistic intervention effects will be low or less than desired. The danger in studies with low statistical power is that interventions that could be beneficial are discarded without adequate testing and may never be considered again. Certainly, many studies do contain appropriate sample size estimates, but many are still too small.

Keywords: Event Rate; Sample Size Calculation; Sample Size Estimate; Annual Event Rate; Internal Pilot (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/978-1-4419-1586-3_8

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