title: Bayesian average error-based approach to sample size calculations for hypothesis testing.
abstract: Under the classical statistical framework, sample size calculations for a hypothesis test of interest maintain prespecified type I and type II error rates. These methods often suffer from several practical limitations. We propose a framework for hypothesis testing and sample size determination using Bayesian average errors. We consider rejecting the null hypothesis, in favor of the alternative, when a test statistic exceeds a cutoff. We choose the cutoff to minimize a weighted sum of Bayesian average errors and choose the sample size to bound the total error for the hypothesis test. We apply this methodology to several designs common in medical studies.
authors.affiliation: Department of Mathematics, Rose-Hulman Institute of Technology, Terre Haute, IN, USA. reyesem@rose-hulman.edu
authors.forename: Eric M
authors.initials: EM
authors.lastname: Reyes
authors.forename: Sujit K
authors.initials: SK
authors.lastname: Ghosh
mesh_terms: D000465:Algorithms; D000924:Anticholesteremic Agents / Q000009:adverse effects / Q000627:therapeutic use; D001499:Bayes Theorem; D002648:Child; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D005464:Fluorobenzenes / Q000009:adverse effects / Q000627:therapeutic use; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000009:adverse effects / Q000627:therapeutic use; D061214:Patient Safety; D011743:Pyrimidines / Q000009:adverse effects / Q000627:therapeutic use; D000068718:Rosuvastatin Calcium; D018401:Sample Size; D013449:Sulfonamides / Q000009:adverse effects / Q000627:therapeutic use
chemical_list: D000924:Anticholesteremic Agents; D005464:Fluorobenzenes; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors; D011743:Pyrimidines; D013449:Sulfonamides; D000068718:Rosuvastatin Calcium