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."

Immunizationisoneofthegreatadvancesinpublichealth. Figure0. 1showsacamel with a solar-powered refrigerator on his back carrying vaccines across a hot desert to the far reaches of civilization. Many vaccines contain live viruses that need to be kept cold, or the vaccine viruses will die, and the vaccines will lose their ability to produce an immune response. Thus a continuous chain of refrigeration, the cold chain, from the origin to delivery of some vaccines needs to be maintained. The inspiration of the camel image is that it represents the dedication of the world to bring vaccines to everyone. The ?rst major success, and the origin of the word vaccination (vacca for cow), was Jenner's introducing cowpox-based vaccine against smallpox in the late 18th century. After nearly a century hiatus, at the end of the 19th century, inoculations against cholera, typhoid, plague (caused by bacteria) and rabies (caused by a virus) were developed. By the early 20th century, statisticians of the stature of Karl Pe- son, Major Greenwood, and Udny Yule were heartily involved in discussions of evaluating these vaccines in the ?eld. In the 1920s, new vaccines included pert- sis, diptheria, tetanus, and bacille Calmette-Guerin ' against tuberculosis. The 1930s saw development of yellow fever, in?uenza, and rickettsia vaccines. After World War II, the advent of cell cultures in which viruses could grow enabled production of polio vaccine and vaccines against measles, mumps, rubella, varicella, and a- novirus, among others (Plotkin et al 2008).

Though the Genome Project will eventually result in the sequencing of the human genome, as well as the genomes of several other organisms, there will still be a need for good statistics for family studies of complex diseases. The papers in this volume are contributions by some of the leading researchers in the field to the current topics in statistical genetics. One section deals with DNA sequence matching and issues related to forensics, while another deals with statistical problems of modeling phylogenies and inferential difficulties related to the complex tree structures produced, as well as the method of coalescence.

Immunizationisoneofthegreatadvancesinpublichealth. Figure0. 1showsacamel with a solar-powered refrigerator on his back carrying vaccines across a hot desert to the far reaches of civilization. Many vaccines contain live viruses that need to be kept cold, or the vaccine viruses will die, and the vaccines will lose their ability to produce an immune response. Thus a continuous chain of refrigeration, the cold chain, from the origin to delivery of some vaccines needs to be maintained. The inspiration of the camel image is that it represents the dedication of the world to bring vaccines to everyone. The ?rst major success, and the origin of the word vaccination (vacca for cow), was Jenner's introducing cowpox-based vaccine against smallpox in the late 18th century. After nearly a century hiatus, at the end of the 19th century, inoculations against cholera, typhoid, plague (caused by bacteria) and rabies (caused by a virus) were developed. By the early 20th century, statisticians of the stature of Karl Pe- son, Major Greenwood, and Udny Yule were heartily involved in discussions of evaluating these vaccines in the ?eld. In the 1920s, new vaccines included pert- sis, diptheria, tetanus, and bacille Calmette-Guerin ' against tuberculosis. The 1930s saw development of yellow fever, in?uenza, and rickettsia vaccines. After World War II, the advent of cell cultures in which viruses could grow enabled production of polio vaccine and vaccines against measles, mumps, rubella, varicella, and a- novirus, among others (Plotkin et al 2008).

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.

Though the Genome Project will eventually result in the sequencing of the human genome, as well as the genomes of several other organisms, there will still be a need for good statistics for family studies of complex diseases. The papers in this volume are contributions by some of the leading researchers in the field to the current topics in statistical genetics. One section deals with DNA sequence matching and issues related to forensics, while another deals with statistical problems of modeling phylogenies and inferential difficulties related to the complex tree structures produced, as well as the method of coalescence.