Innovative Bayesian Methods for Biostatistics and Epidemiology

Paul Gustafson, Shahadut Hossain, Lawrence McCandless

    Research output: Chapter in Book/Report/Conference proceedingChapter

    3 Citations (Scopus)


    Complex data and models now pervade biostatistics and epidemiology. Increasingly, Bayesian methods are seen as desirable tools to tame this complexity and make principled inferences from the data at hand. In this chapter we try to convey the flavor of what Bayesian methods have to offer, by describing a number of applications of Bayesian methods to health research. We emphasize the strengths of these approaches, and points of departure from non-Bayesian techniques.

    Original languageEnglish
    Title of host publicationBayesian Thinking Modeling and Computation
    EditorsD.K. Dey, C.R. Rao
    Number of pages30
    Publication statusPublished - Dec 1 2005

    Publication series

    NameHandbook of Statistics
    ISSN (Print)0169-7161

    ASJC Scopus subject areas

    • Statistics and Probability
    • Modelling and Simulation
    • Applied Mathematics


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