SKEPTICAL AND OPTIMISTIC ROBUST PRIORS FOR CLINICAL TRIALS
A useful technique from the subjective Bayesian viewpoint, is to ask the subject matter researchers and other parties involved, such as pharmaceutical companies and regulatory bodies, for reasonable optimistic and pessimistic priors regarding the effectiveness of a new treatment. Up to now, the prop...
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Veröffentlicht in: | Revista Colombiana de estadística 2011-06, Vol.34 (2), p.333 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng ; por |
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Zusammenfassung: | A useful technique from the subjective Bayesian viewpoint, is to ask the subject matter researchers and other parties involved, such as pharmaceutical companies and regulatory bodies, for reasonable optimistic and pessimistic priors regarding the effectiveness of a new treatment. Up to now, the proposed skeptical and optimistic priors have been limited to conjugate priors, though there is no need for this limitation. The same reasonably adversarial points of view can take with robust priors. Robust priors permit a much faster and efficient resolution of the disagreement between the conclusions based on skeptical and optimistic priors. As a consequence, robust Bayesian clinical trials tend to be shorter. Our proposal in this paper is to use Cauchy and intrinsic robust priors for both skeptical and optimistic priors leading to results more closely related with the sampling data when prior and data are in conflict. In other words, the use of robust priors removes the dogmatism implicit in conjugate priors. Dogmatism here has very precise meaning: Conjugate priors affect the posterior conclusions by a fixed rate, regardless if there is a conflict between prior and data. Robust priors are automatically discounted by Bayes Theorem in the presence of conflict. |
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ISSN: | 0120-1751 2389-8976 |