Bayesian topics in biostatistics : treatment selection, sample size, power, and misclassification.




Doty, Tave Parker.

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Bayesian methodology is implemented to investigate three problems in biostatistics. The first problem considers using biomarkers to select optimal treatments for individual patients. A Bayesian adaptation of the selection impact (SI) curve developed by Pepe and Song (2004) is investigated. The second problem considers a Bayesian approach for determining specific sample sizes to achieve a desired range of power for fixed-dose combination drug trials. Sidik and Jonkman (2003) developed a sample size formula using the intersection-union test for testing the efficacy of combination drugs. Our results are compared to their frequentist approach. The third problem considers response misclassification in fixed-dose combination drug trials under two scenarios: when the sensitivity and specificity are known, and when the sensitivity and specificity are unknown but have specified informative prior structures.



Bayesian statistics., Biomarkers., Combination drugs., Treatment selection., Sample size., Power., Misclassification.