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141 by B.C. Hiest is a Medicine article available to read on EtoBox.
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The type I and type II error rates for clinical trials designed using this approach are determined by the criteria for significance at each analysis and the sample size. While statistical significance is the primary criterion for stopping at each analysis, the total number of treatment failures occurring in the ongoing trial is not considered. Bayesian decision theory can be used to design trials that balance the goals of minimizing the risk of error in identifying the better treatment and of optimizing the outcomes of the subjects. Our objectives were (1) to design group sequential trials for diseases with binary outcomes that consider, at each analysis, the costs associated with patient enrollment, with the risk of drawing an incorrect conclusion, and with patient harm; (2) to compare the required number of patients and error risks of trials designed with and without consideration of patient harm; and (3) to examine the resulting decision rules to determine what interim trial results would lead to different decisions based on the consideration of patient harm. Methods: We used Metropolis-Hastings sampling and backward induction to determine optimal trial designs. The loss functio
Who reads 141?
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- Author
- B.C. Hiest
- Publisher
- Elsevier Science; Elsevier ; Mosby Inc.; Elsevier BV (ISSN 1097-6760)
- Published
- 2006
- Language
- JA
- Field
- Medicine (Health Sciences)