Journal Article10.1111/J.1467-9876.2004.0D490.X
Optimal predictive sample size for case-control studies
TL;DR: In this article, sample size determination and allocation criteria for both interval estimation and hypothesis testing were employed to determine the sample size and proportions of units to be assigned to cases and controls for planning a study on the association between the incidence of a non-Hodgkin's lymphoma and exposition to pesticides by eliciting prior information from a previous study.
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Abstract: Summary. The identification of factors that increase the chances of a certain disease is one of the classical and central issues in epidemiology. In this context, a typical measure of the association between a disease and risk factor is the odds ratio. We deal with design problems that arise for Bayesian inference on the odds ratio in the analysis of case–control studies. We consider sample size determination and allocation criteria for both interval estimation and hypothesis testing. These criteria are then employed to determine the sample size and proportions of units to be assigned to cases and controls for planning a study on the association between the incidence of a non-Hodgkin's lymphoma and exposition to pesticides by eliciting prior information from a previous study.
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Citations
Assurance in clinical trial design
TL;DR: The theory of assurance is extended to two-sided testing and equivalence trials and it is shown that assurance is straightforward to compute in some simple problems of normal, binary and gamma distributed data, and that the method is not restricted to simple conjugate prior distributions for parameters.
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Bayesian Sample Size Determination for Case-Control Studies
TL;DR: In this paper, the authors investigate Bayesian sample size determination and the control-to-case ratio for case-control studies, when interval estimation is the goal of the eventual statistical analysis.
Bayesian Analysis of Case-Control Studies
TL;DR: A review of existing Bayesian work for analyzing case-control data, some recent advancements and possibilities for future research can be found in this article, with a focus on the use of hierarchical models.
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Case-Control Studies of Gene-Environment Interaction: Bayesian Design and Analysis
TL;DR: A proper full Bayesian approach is proposed for analyzing studies of gene–environment interaction using data from a large ongoing case–control study of colorectal cancer investigating the interaction of N‐acetyl transferase type 2 with smoking and red meat consumption.
Sample size calculations for disease freedom and prevalence estimation surveys.
TL;DR: A Bayesian approach to sample size calculations for studies designed to estimate disease prevalence that uses a hierarchical model for estimating the proportion of infected clusters (cluster‐level prevalence) within a country or region is developed.
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References
Categorical Data Analysis
TL;DR: In this article, categorical data analysis was used for categorical classification of categorical categorical datasets.Categorical Data Analysis, categorical Data analysis, CDA, CPDA, CDSA
15.1K
•Book
Statistical Decision Theory and Bayesian Analysis
James O. Berger
- 22 Dec 2012
TL;DR: An overview of statistical decision theory, which emphasizes the use and application of the philosophical ideas and mathematical structure of decision theory.
8.4K
Bayesian Experimental Design: A Review
TL;DR: This paper reviews the literature on Bayesian experimental design, both for linear and nonlinear models, and presents a uniied view of the topic by putting experimental design in a decision theoretic framework.
Applied Statistical Decision Theory.
TL;DR: In this paper, the authors describe the nature of decision problems in drilling for gas and oil, a business situation where uncertainties are exceptionally great, and describe how businessmen actually make drilling decisions in the face of these uncertainties.
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