title: Finding Alternatives to the Dogma of Power Based Sample Size Calculation: Is a Fixed Sample Size Prospective Meta-Experiment a Potential Alternative?
abstract: Sample sizes for randomized controlled trials are typically based on power calculations. They require us to specify values for parameters such as the treatment effect, which is often difficult because we lack sufficient prior information. The objective of this paper is to provide an alternative design which circumvents the need for sample size calculation. In a simulation study, we compared a meta-experiment approach to the classical approach to assess treatment efficacy. The meta-experiment approach involves use of meta-analyzed results from 3 randomized trials of fixed sample size, 100 subjects. The classical approach involves a single randomized trial with the sample size calculated on the basis of an a priori-formulated hypothesis. For the sample size calculation in the classical approach, we used observed articles to characterize errors made on the formulated hypothesis. A prospective meta-analysis of data from trials of fixed sample size provided the same precision, power and type I error rate, on average, as the classical approach. The meta-experiment approach may provide an alternative design which does not require a sample size calculation and addresses the essential need for study replication; results may have greater external validity.
authors.affiliation: INSERM, U1153, Paris, France.|CHRU, Tours, France.|INSERM CIC 1415, Tours, France.
authors.forename: Elsa
authors.initials: E
authors.lastname: Tavernier
authors.affiliation: INSERM, U1153, Paris, France.|Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, United States of America.
authors.forename: Ludovic
authors.initials: L
authors.lastname: Trinquart
authors.affiliation: INSERM, U1153, Paris, France.|CHRU, Tours, France.|INSERM CIC 1415, Tours, France.|Université François-Rabelais de Tours, Tours, France.
authors.forename: Bruno
authors.initials: B
authors.lastname: Giraudeau
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D015233:Models, Statistical; D012107:Research Design; D018401:Sample Size; D013223:Statistics as Topic