Forecasting Product Liability Claims
Epidemiology and Modeling in the Manville Asbestos Case. Vorwort: Weinstein, J.B.
(Sprache: Englisch)
This selection of papers encompasses recent methodological advances in several important areas, such as multivariate failure time data and interval censored data, as well as innovative applications of the existing theory and methods. Using a rigorous...
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This selection of papers encompasses recent methodological advances in several important areas, such as multivariate failure time data and interval censored data, as well as innovative applications of the existing theory and methods. Using a rigorous account of statistical forecasting efforts that led to the successful resolution of the John-Manville asbestos litigation, the models in this volume can be adapted to forecast industry-wide asbestos liability. More generally, because the models are not overly dependent on the U.S. legal system and the role of asbestos, this volume will be of interest in other product liability cases, as well as similar forecasting situations for a range of insurable or compensational events. Throughout the text, the emphasis is on the iterative nature of model building and the uncertainty generated by lack of complete knowledge of the injury process. This uncertainty is balanced against the court's need for a definitive settlement, and how these opposing principles can be reconciled. A valuable reference for researchers and practitioners in the field of survival analysis., such as multivariate failure time data and interval censored data, as well as innovative applications of the existing theory and methods. Using a rigorous account of statistical forecasting efforts that led to the successful resolution of the John-Manville asbestos litigation, the models in this volume can be adapted to forecast industry-wide asbestos liability. More generally, because the models are not overly dependent on the U.S. legal system and the role of asbestos, this volume will be of interest in other product liability cases, as well as similar forecasting situations for a range of insurable or compensational events. Throughout the text, the emphasis is on the iterative nature of model building and the uncertainty generated by lack of complete knowledge of the injury process. This uncertainty is balanced against the court's need for a definitive settlement, and how these opposing principles can be reconci
Klappentext zu „Forecasting Product Liability Claims “
I write this foreword for two reasons: first, to acknowledge the gratitude of our court system to scientists willing to lend their talents to forensic tasks, and of myself, in particular, for the pathbreaking work of Eric Stallard, Kenneth G. Manton, and Joel E. Cohen in the Manville Asbestos Case; and second, because their work suggests both great strength and utility in their statisti cally based design and its limitations in predicting events strongly affected by political and social choices that are difficult to foretell as well as by de mographic and epidemiologic factors that can be prophesied with somewhat more confidence - at least in the short term. It is by now almost axiomatic that almost every important litigation in the United States requires experts to help judges and juries arrive at an under standing of the case sufficient to permit a sensible resolution within the flexible scope of our rules of law. The Supreme Court has laid down useful rough cri teria for the courts in assessing the capability of proffered experts beginning 1 with the Daubert line of cases. It has also allowed the courts to appoint ex 2 perts to supplement those designated by the parties. Dr. Joel E. Cohen and Professor Margaret E. Berger were appointed by me in the Manville asbestos cases pursuant to Rule 706 of the Federal Rules of Evidence to help project future claims. Discovery provisions have improved utilization of experts by 3 requiring advance reports and depositions.
Inhaltsverzeichnis zu „Forecasting Product Liability Claims “
1 Overview.- 2 Epidemiology of Asbestos-Related Diseases.- 3 Forecasts Based on Direct Estimates of Exposure.- 4 Forecasts Based on Indirect Estimates of Exposure.- 5 Uncertainty in Forecasts Based on Indirect Estimates.- 6 Updated Forecasts Based on Indirect Estimates of Exposure.- 7 Uncertainty in Updated Forecasts.- 8 Forecasts Based on a Hybrid Model.- 9 Uncertainty in Forecasts Based on a Hybrid Model.- 10 Conclusions and Implications.- References.
Autoren-Porträt von Eric Stallard, Kenneth G. Manton, Joel E. Cohen
Kenneth G. Manton, Ph.D. is Research Professor, Research Director, and Director of the Center for Demographic Studies at Duke University, and Medical Research Professor at Duke University Medical Center's Department of Community and Family Medicine. Dr. Manton is also a Senior Fellow of the Duke University Medical Center's Center for the Study of Aging and Human Development. His research interests include mathematical models of human aging, mortality, and chronic disease. He was the 1990 recipient of the Mindel C. Sheps Award in Mathematical Demography presented by the Population Association of America; and in 1991 he received the Allied-Signal Inc. Achievement Award in Aging administered by the Johns Hopkins Center on Aging.Joel E. Cohen, Ph.D., Dr. P.H., is Professor of Population, and Head of the Laboratory of Populations, Rockefeller University. He also is Professor of Populations at Columbia University. His research interests include the demography, ecology, epidemiology, and social organization of human and non-human populations, and related mathematical concepts. In 1981, he was elected Fellow of the MacArthur and Guggeneheim Foundations. He was the 1992 recipient of the Mindel C. Sheps Award in Mathematical Demography presented by the Population Association of America; and in 1994, he received the Distinguished Statistical Ecologist Award at the Sixth International Congress of Ecology.
Bibliographische Angaben
- Autoren: Eric Stallard , Kenneth G. Manton , Joel E. Cohen
- 2010, Softcover reprint of hardcover 1st ed. 2004, XXX, 394 Seiten, Masse: 1,5 x 2,4 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 144192860X
- ISBN-13: 9781441928603
Sprache:
Englisch
Pressezitat
From the reviews: "This monograph shows then epidemiological prediction in action and is more eloquent than most textbooks as regards to methodology and difficulties encountered with field data. It should interest far outside the circle of asbestos-related epidemiology because of its rigorous exposition, the relevance of its questions, the adequacy of the solutions offered, the discussion of its results, and its legal, financial, and human consequences." Mathematical Population Studies, 12:181-182, 2005
"Over 750,000 claimants have filed suit ... for illnesses and deaths related to exposure to asbestos, and at least 65 companies had been driven to bankruptcy; these numbers continue to grow. ... This work led to substantial advances in the art of forecasting the number, timing, and nature of new claims. The authors present a lucid explanation of these advances and a description of how the matters in litigation have been settled. The presiding judge, Jack Weinstein, has contributed an informative preface ... ." (J.C. Bailar, Short Book Reviews Publication of the International Statistical Institute, Vol. 25 (1), 2005)
"Demographers Eric Stallard, Kenneth Manton and Joel Cohen use a risk assessment framework to estimate the numbers of claims expected during the period between 1990 and 2049 for asbestos-related disease among men exposed to ... asbestos products. ... Forecasting Product Liability Claims is notable for its illustration of the possibility of using epidemiologic and demographic methods to develop models for broad policy purposes. ... It is formula-rich and dense in its description of data sources and the machinery of the models, as it should be." (Jonathan M. Samet, Science-AAAS, May, 2006)
"This book summarizes the statistical models for projecting the number, timing, and nature of future claims, and it discusses how these predictions are used in developing a fair and equitable distribution of insufficientfunds.
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... This book provides a fascinating account of how predication models are used to solve a very-real problem. It makes wonderful reading for statisticians interested in prediction problems, epidemiologists, actuaries, and lawyers involved in product liability suits and having to predict the number of possible litigants." (Johannes Ledolter, Zentralblatt MATH, Vol. 1099 (1), 2007)
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