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.

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• 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

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.

Select Guide Rating

• 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

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.

Select Guide Rating

• 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