Statistical Models in Epidemiology, the Environment, and Clinical Trials / Edition 1

by M.Elizabeth Halloran, Donald Berry

Overview

This IMA Volume in Mathematics and its Applications STATISTICAL MODELS IN EPIDEMIOLOGY, THE ENVIRONMENT,AND CLINICAL TRIALS is a combined proceedings on "Design and Analysis of Clinical Trials" and "Statistics and Epidemiology: Environment and Health. " This volume is the third series based on the proceedings of a very successful 1997 IMA Summer Program on "Statistics in the Health Sciences. " I would like to thank the organizers: M. Elizabeth Halloran of Emory University (Biostatistics) and Donald A. Berry of Duke University (Insti­ tute of Statistics and Decision Sciences and Cancer Center Biostatistics) for their excellent work as organizers of the meeting and for editing the proceedings. I am grateful to Seymour Geisser of University of Minnesota (Statistics), Patricia Grambsch, University of Minnesota (Biostatistics); Joel Greenhouse, Carnegie Mellon University (Statistics); Nicholas Lange, Harvard Medical School (Brain Imaging Center, McLean Hospital); Barry Margolin, University of North Carolina-Chapel Hill (Biostatistics); Sandy Weisberg, University of Minnesota (Statistics); Scott Zeger, Johns Hop­ kins University (Biostatistics); and Marvin Zelen, Harvard School of Public Health (Biostatistics) for organizing the six weeks summer program. I also take this opportunity to thank the National Science Foundation (NSF) and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr.

Product Details

ISBN-13:	9780387989242
Publisher:	Springer New York
Publication date:	10/29/1999
Series:	The IMA Volumes in Mathematics and its Applications , #116
Edition description:	2000
Pages:	283
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models.- Marginal structural models versus structural nested models as tools for causal inference.- Nonparametric locally efficient estimation of the treatment specific survival distribution with right censored data and covariates in observational studies.- Estimation of disease rates in small areas: A new mixed model for spatial dependence.- Markov chain Monte Carlo methods for clustering in case event and count data in spatial epidemiology.- A simulation study of the epidemiological impact of air pollution: Diagnostics of the confounding effects for generalized linear models.- The use of reference priors and Bayes factors in the analysis of clinical trials.- Surrogate endpoints in cancer clinical trials.- List of Participants.