Bayesian average error-based approach to sample size calculations for hypothesis testing.
J Biopharm Stat
; 23(3): 569-88, 2013 May.
Article
em En
| MEDLINE
| ID: mdl-23611196
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Teorema de Bayes
/
Tamanho da Amostra
Limite:
Child
/
Humans
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article