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

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(More customer reviews)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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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.

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