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Forecasting Product Liability Claims: Epidemiology and Modeling in the Manville Asbestos Case (Statistics for Biology and Health)
 
 
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Forecasting Product Liability Claims: Epidemiology and Modeling in the Manville Asbestos Case (Statistics for Biology and Health) [Hardcover]

Eric Stallard (Author), Kenneth G. Manton (Author), Joel E. Cohen (Author), J.B. Weinstein (Foreword)
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Book Description

October 25, 2004 Statistics for Biology and Health
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.

Editorial Reviews

Review

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 insufficient funds. … 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)

From the Back Cover

 This volume presents a rigorous account of statistical forecasting efforts that led to the successful resolution of the Johns-Manville asbestos litigation. This case, taking 12 years to reach settlement, is expected to generate nearly 500,000 claims at a total nominal value of over $34 billion. The forecasting task, to project the number, timing, and nature of claims for asbestos-related injuries from a set of exposed persons of unknown size, is a general problem: 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 as a dangerous/defective product, this volume will be of interest in other product liability cases, as well as similar forecasting situations for a range of insurable or compensable events. The volume stresses 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 the volume addresses how these opposing principles can be reconciled.

The volume is written for a broad audience of actuaries, biostatisticians, demographers, economists, epidemiologists, environmental health scientists, financial analysts, industrial-risk analysts, investment analysts, occupational health analysts, product liability analysts, and statisticians. The modest prerequisites include basic concepts of statistics, calculus, and matrix algebra. Care is taken that readers without specialized knowledge in these areas can understand the rationale for specific applications of advanced methods. As a consequence, this volume will be an indispensable reference for all whose work involves these topics.

Eric Stallard, A.S.A., M.A.A.A., is Research Professor and Associate Director of the Center for Demographic Studies at Duke University. He is a Member of the American Academy of Actuaries and an Associate of the Society of Actuaries. He serves on the American Academy of Actuaries Committees on Long Term Care and Social Insurance. He also serves on the Society of Actuaries’ Long Term Care Experience Committee. His research interests include modeling and forecasting for medical demography and health actuarial practice. He was the 1996 winner of the National Institute on Aging’s James A. Shannon Director’s Award.

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.

 


Product Details

  • Hardcover: 423 pages
  • Publisher: Springer; 1 edition (October 25, 2004)
  • Language: English
  • ISBN-10: 0387949879
  • ISBN-13: 978-0387949871
  • Product Dimensions: 9.5 x 6.4 x 1.1 inches
  • Shipping Weight: 1.7 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,605,212 in Books (See Top 100 in Books)

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1 of 1 people found the following review helpful:
5.0 out of 5 stars The Details Make the Difference, August 30, 2006
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Lawrence Curtis (Washington, D.C. USA) - See all my reviews
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This review is from: Forecasting Product Liability Claims: Epidemiology and Modeling in the Manville Asbestos Case (Statistics for Biology and Health) (Hardcover)
Reading "Forecasting Product Liability Claims" with the eyes of an attorney involved in the management of mass tort litigation settlements is a daunting task because the text contains very detailed statistical formulae and concepts. However, it is the clarity with which the concepts are explained that allows the non-statistician who has interest to follow the logic. Understanding how the statistics professional accumulates and finds understanding in the seemingly unassociated data should give great insight to the legal professional, whether lawyer or judge, who needs to bring individual justice to thousands of claimants. The introduction by Judge Weinstein is the icing on a rich slowly digested cake for the legal professional.
Lawrence Curtis, General Counsel, Mass Tort Settlements Services
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Inside This Book (learn more)
First Sentence:
This chapter provides background to the Manville asbestos case, an overview of our modeling task, the results, the range of uncertainty, the setting of payout percentages, the need to monitor the future claim process, and the implications of our results for asbestos product liability litigation. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
claim filing rates, noncancer claims, mesothelioma claims, surviving exposed population, asbestosis prevalence, mesothelioma ratio, mesothelioma cases, cancer projections, asbestosis deaths, exposed workforce, mesothelioma incidence, exposed population estimates, incidence counts, validated disease, insulation workers, mesothelioma deaths, asbestosis claims, lung cancer claims, noncancer causes, claim projections, time since first exposure, mesothelioma risks, diagnosis counts, claim depletion, asbestos defendants
Key Phrases - Capitalized Phrases (CAPs): (learn more)
United States, Projection Type, Projection Interval, North American, World War, Trust Distribution Process, Change From Table, Johns-Manville Corporation, National Cancer Institute, Quinquennial Dates of Claim, Projected Difference, Recode Category Type Description, Model Date of Claim, Unknown Total, Walker's Task, End Results Program, Public Use Data, Asbestos Abatement, Comparison of Tables, Data File, Los Angeles County, Model Table, Resource Planning Corporation, Indirect Estimates of Exposure, Public Use Mortality Files
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