Sample Size
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 s
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Sample Size
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.” The situation was not much improved in 1994, when a similar survey found only 16% of negative trials had 80% power for a 25% effect, and only 36% for a 50% effect [2]. 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 in spite of many years of critical review many are still too small [3, 4]. This chapter presents an overview of sample size estimation with some details. Several general discussions of sample size can be found elsewhere [5–21]. For example, Lachin [11] and Donner [9] have each written a more technical discussion of this topic. For most of the chapter, the focus is on sample size where the study is randomizing individuals. In the some sections, the concept of sample size for randomizing clusters of individuals or organs within individuals is presented.
© Springer International Publishing Switzerland 2015 L.M. Friedman et al., Fundamentals of Clinical Trials, DOI 10.1007/978-3-319-18539-2_8
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8 Sample Size
Fundamental Point Clinical trials should have sufficient statistical power to detect differences between groups considered to be of clinical importance. Therefore, calculation of sample size with provision for adequate levels of significance and power is an essential part of planning. Before a discussion of sample size and power calculations, it must be emphasized that, for several reasons, a sample size calculation provides only an estimate of the needed size of a trial [6]. First, parameters used in the calculation are estimates, and as such, have an element of uncertainty. Often these estimates are based on small studies. Second, the estimate of the relative effectiveness of the intervention over the control and other estimates may be based on a population different from that intended to be studied. Third, the effectiveness is often overestimated since published pilot studies may be highly
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