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Statistical Models in Epidemiology, the Environment, and Clinical Trials (Hardcover, 2000 ed.)
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Statistical Models in Epidemiology, the Environment, and Clinical Trials (Hardcover, 2000 ed.)
Series: The IMA Volumes in Mathematics and its Applications, 116
Expected to ship within 10 - 15 working days
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This volume contains refereed papers by participants in the two
weeks on Clinical Trials and one week on Epidemiology and the
Environment held as part of the six weeks workshop on Statistics in
the Health Sciences Applications at the Institute for Mathematics
and its Applications (IMA) in the summer of 1997. Donald Berry was
in charge of the weeks on clinical trials, and Elizabeth Halloran
organized the week on epidemiology and the environment. The
collection includes a major contribution from Jamie Robins, Andrea
Rotnitzky, and Daniel Scharfstein on sensitivity analysis for
selection bias and unmeasured confounding in missing data and
causal and inference models. In another paper, Jamie Robins
presents a new class of causal models called marginal structural
models. Alan Hubbard, Mark van der Laan, and Jamie Robins present a
methodology for consistent and efficient estimation of
treatment-specific survival functions in observational settings.
Brian Leroux, Xingye Lei, and Norman Breslow present a new mixed
model for spatial dependence for estimating disease rates in small
areas. Andrew Lawson and Allan Clark demonstrate Markov Chain Monte
Carlo methods for clustering in spatial epidemiology. Colin Chen,
David Chock, and Sandra Winkler present a simulation study
examining confounding in estimation of the epidemiologic effect of
air pollution. Dalene Stangl discusses issues in the use of
reference priors and Bayes factors in analyzing clinical trials.
Stephen George reviews the role of surrogate endpoints in cancer
clinical trials.
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