Uncertainty Modeling in Dose Response

Bench Testing Environmental Toxicity

Inbunden, Engelska, 2009

2 139 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

A valuable guide to understanding the problem of quantifying uncertainty in dose response relations for toxic substances In today's scientific research, there exists the need to address the topic of uncertainty as it pertains to dose response modeling. Uncertainty Modeling in Dose Response is the first book of its kind to implement and compare different methods for quantifying the uncertainty in the probability of response, as a function of dose. This volume gathers leading researchers in the field to properly address the issue while communicating concepts from diverse viewpoints and incorporating valuable insights. The result is a collection that reveals the properties, strengths, and weaknesses that exist in the various approaches to bench test problems.This book works with four bench test problems that were taken from real bioassay data for hazardous substances currently under study by the United States Environmental Protection Agency (EPA). The use of actual data provides readers with information that is relevant and representative of the current work being done in the field. Leading contributors from the toxicology and risk assessment communities have applied their methods to quantify model uncertainty in dose response for each case by employing various approaches, including Benchmark Dose Software methods, probabilistic inversion with isotonic regression, nonparametric Bayesian modeling, and Bayesian model averaging. Each chapter is reviewed and critiqued from three professional points of view: risk analyst/regulator, statistician/mathematician, and toxicologist/epidemiologist. In addition, all methodologies are worked out in detail, allowing readers to replicate these analyses and gain a thorough understanding of the methods.Uncertainty Modeling in Dose Response is an excellent book for courses on risk analysis and biostatistics at the upper-undergraduate and graduate levels. It also serves as a valuable reference for risk assessment, toxicology, biostatistics, and environmental chemistry professionals who wish to expand their knowledge and expertise in statistical dose response modeling problems and approaches.

Produktinformation

Utgivningsdatum2009-07-30
Mått165 x 241 x 18 mm
Vikt481 g
FormatInbunden
SpråkEngelska
SerieStatistics in Practice
Antal sidor248
FörlagJohn Wiley & Sons Inc
ISBN9780470447505

Tillhör följande kategorier

Miljövetenskap och miljöpolitik inom Naturvetenskap och teknik
Kemi inom Naturvetenskap och teknik
Matematik inom Naturvetenskap och teknik
Farmakologi inom Medicin

ROGER M. COOKE, PhD, is Professor in the Department of Mathematics at Delft University of Technology, the Netherlands, and Chauncey Starr Senior Fellow for Risk Analysis at Resources for the Future, a nonprofit organization based in Washington, D.C., that conducts independent research on environmental, energy, and natural resource issues. Recognized as one of the world's leading authorities on mathematical modeling of risk and uncertainty, Dr. Cooke's research has widely influenced risk assessment methodology, particularly in the areas of expert judgment and uncertainty analysis.

Acknowledgments ixContributors xiIntroduction 1Roger M. Cooke and Margaret MacDonell1 Analysis of Dose–Response Uncertainty Using Benchmark Dose Modeling 17Jeff SwartoutComment: The Math/Stats Perspective on Chapter 1: Hard Problems Remain 34Allan H. MarcusComment: EPI/TOX Perspective on Chapter 1: Re-formulating the Issues 37Jouni T. TuomistoComment: Regulatory/Risk Perspective on Chapter 1: A Good Baseline 42Weihsueh ChiuComment: A Question Dangles 44David BussardComment: Statistical Test for Statistics-as-Usual Confi dence Bands 45Roger M. CookeResponse to Comments 47Jeff Swartout2 Uncertainty Quantifi cation for Dose–Response Models Using Probabilistic Inversion with Isotonic Regression: Bench Test Results 51Roger M. CookeComment: Math/Stats Perspective on Chapter 2: Agreement and Disagreement 82Thomas A. LouisComment: EPI/TOX Perspective on Chapter 2: What Data Sets Per se Say 87Lorenz RhombergComment: Regulatory/Risk Perspective on Chapter 2: Substantial Advances Nourish Hope for Clarity? 97Rob GobleComment: A Weakness in the Approach? 105Jouni T. TuomistoResponse to Comments 107Roger Cooke3 Uncertainty Modeling in Dose Response Using Nonparametric Bayes: Bench Test Results 111Lidia Burzala and Thomas A. MazzuchiComment: Math/Stats Perspective on Chapter 3: Nonparametric Bayes 147Roger M. CookeComment: EPI/TOX View on Nonparametric Bayes: Dosing Precision 150Chao W. ChenComment: Regulator/Risk Perspective on Chapter 3: Failure to Communicate 153Dale HattisResponse to Comments 160Lidia Burzala4 Quantifying Dose–Response Uncertainty Using Bayesian Model Averaging 165Melissa Whitney and Louise RyanComment: Math/Stats Perspective on Chapter 4: Bayesian Model Averaging 180Michael MessnerComment: EPI/TOX Perspective on Chapter 4: Use of Bayesian Model Averaging for Addressing Uncertainties in Cancer Dose–Response Modeling 183Margaret ChuComment: Regulatorary/Risk Perspective on Chapter 4: Model Averages, Model Amalgams, and Model Choice 185Adam M. FinkelResponse to Comments 194Melissa Whitney and Louise Ryan5 Combining Risks from Several Tumors Using Markov Chain Monte Carlo 197Leonid Kopylev, John Fox, and Chao Chen6 Uncertainty in Dose Response from the Perspective of Microbial Risk 207P. F. M. Teunis7 Conclusions 217David Bussard, Peter Preuss, and Paul WhiteAuthor Index 225Subject Index 229