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• W2035863199 abstract "Abstract In the Bayesian framework, quantified judgments about uncertainty are an indispensable input to methods of statistical inference and decision. Ultimately, all components of the formal mathematical models underlying inferential procedures represent quantified judgments. In this study, the focus is on just one component, the prior distribution, and on some of the problems of assessment that arise when a person tries to express prior distributions in quantitative form. The objective is to point toward assessment procedures that can actually be used. One particular type of statistical problem is considered and several techniques of assessment are presented, together with the necessary instruction so that these techniques can be understood and applied. A questionnaire is developed and used in a study in which people actually assess prior distributions. The results indicate that, by and large, it is feasible to question people about subjective prior probability distributions, although this depends on t..." @default.
• W2035863199 created "2016-06-24" @default.
• W2035863199 creator A5004546990 @default.
• W2035863199 date "1967-09-01" @default.
• W2035863199 modified "2023-10-18" @default.
• W2035863199 title "The Assessment of Prior Distributions in Bayesian Analysis" @default.
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• W2035863199 doi "https://doi.org/10.2307/2283671" @default.
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