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Sample size determination for at test given at value from a previous study: A FORTRAN 77 program
Authors:Raphael Gillett
Institution:(1) EA 4275 “Biostatistique, recherche clinique et mesures subjectives en sant?”, Facult? de Pharmacie, Universit? de Nantes, 1 rue Gaston Veil, 44035 Nantes Cedex 1, France;(2) Plateforme de Biom?trie, Cellule de promotion de la recherche clinique, CHU de Nantes, France;(3) University of Reims Champagne-Ardenne, Faculty of medicine - EA 3797, 35 rue Cognacq Jay, F-51095 Reims, France;(4) Department of Physical Medicine and Rehabilitation, Sebastopol Hospital, 48 rue de S?bastopol, F-51092 Reims, France;(5) Nancy-Universit?, Paul Verlaine Metz University, Paris Descartes University, EA, 4360 Apemac, Nancy, France;(6) INSERM 669, Universit? Paris-Sud, and Universit? Paris Descartes, Paris, France;(7) AP-HP, H?pital Paul Brousse, D?partement de sant? publique, Villejuif, France
Abstract:When uncertain about the magnitude of an effect, researchers commonly substitute in the standard sample-size-determination formula an estimate of effect size derived from a previous experiment. A problem with this approach is that the traditional sample-size-determination formula was not designed to deal with the uncertainty inherent in an effect-size estimate. Consequently, estimate-substitution in the traditional sample-size-determination formula can lead to a substantial loss of power. A method of sample-size determination designed to handle uncertainty in effect-size estimates is described. The procedure uses thet value and sample size from a previous study, which might be a pilot study or a related study in the same area, to establish a distribution of probable effect sizes. The sample size to be employed in the new study is that which supplies an expected power of the desired amount over the distribution of probable effect sizes. A FORTRAN 77 program is presented that permits swift calculation of sample size for a variety oft tests, including independentt tests, relatedt tests,t tests of correlation coefficients, andt tests of multiple regressionb coefficients.
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