TY - CHAP
T1 - Innovative Bayesian Methods for Biostatistics and Epidemiology
AU - Gustafson, Paul
AU - Hossain, Shahadut
AU - McCandless, Lawrence
PY - 2005/12/1
Y1 - 2005/12/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=33748303473&partnerID=8YFLogxK
U2 - 10.1016/S0169-7161(05)25026-5
DO - 10.1016/S0169-7161(05)25026-5
M3 - Chapter
AN - SCOPUS:33748303473
SN - 9780444515391
T3 - Handbook of Statistics
SP - 763
EP - 792
BT - Bayesian Thinking Modeling and Computation
A2 - Dey, D.K.
A2 - Rao, C.R.
ER -