LEADER 04409nam 2200649Ia 450 001 9910143128803321 005 20230721021805.0 010 $a1-282-69103-1 010 $a9786612691034 010 $a0-470-48140-4 010 $a0-470-48139-0 035 $a(CKB)1000000000765798 035 $a(EBL)469297 035 $a(OCoLC)647810817 035 $a(SSID)ssj0000263931 035 $a(PQKBManifestationID)11217408 035 $a(PQKBTitleCode)TC0000263931 035 $a(PQKBWorkID)10283277 035 $a(PQKB)11582180 035 $a(MiAaPQ)EBC469297 035 $a(Au-PeEL)EBL469297 035 $a(CaPaEBR)ebr10308393 035 $a(CaONFJC)MIL269103 035 $a(EXLCZ)991000000000765798 100 $a20081202d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aUncertainty modeling in dose response$b[electronic resource] $ebench testing environmental toxicity /$fRoger M. Cooke 210 $aHoboken $cWiley$dc2009 215 $a1 online resource (246 p.) 225 1 $aStatistics in Practice ;$vv.74 300 $aDescription based upon print version of record. 311 $a0-470-44750-8 320 $aIncludes bibliographical references and index. 327 $aUNCERTAINTY MODELING IN DOSE RESPONSE; CONTENTS; Acknowledgments; Contributors; Introduction; 1 Analysis of Dose-Response Uncertainty Using Benchmark Dose Modeling; Comment: The Math/Stats Perspective on Chapter 1: Hard Problems Remain; Comment: EPI/TOX Perspective on Chapter 1: Re-formulating the Issues; Comment: Regulatory/Risk Perspective on Chapter 1: A Good Baseline; Comment: A Question Dangles; Comment: Statistical Test for Statistics-as-Usual Confidence Bands; Response to Comments 327 $a2 Uncertainty Quantification for Dose-Response Models Using Probabilistic Inversion with Isotonic Regression: Bench Test ResultsComment: Math/Stats Perspective on Chapter 2: Agreement and Disagreement; Comment: EPI/TOX Perspective on Chapter 2: What Data Sets Per se Say; Comment: Regulatory/Risk Perspective on Chapter 2: Substantial Advances Nourish Hope for Clarity?; Comment: A Weakness in the Approach?; Response to Comments; 3 Uncertainty Modeling in Dose Response Using Nonparametric Bayes: Bench Test Results; Comment: Math/Stats Perspective on Chapter 3: Nonparametric Bayes 327 $aComment: EPI/TOX View on Nonparametric Bayes: Dosing PrecisionComment: Regulator/Risk Perspective on Chapter 3: Failure to Communicate; Response to Comments; 4 Quantifying Dose-Response Uncertainty Using Bayesian Model Averaging; Comment: Math/Stats Perspective on Chapter 4: Bayesian Model Averaging; Comment: EPI/TOX Perspective on Chapter 4: Use of Bayesian Model Averaging for Addressing Uncertainties in Cancer Dose-Response Modeling; Comment: Regulatorary/Risk Perspective on Chapter 4: Model Averages, Model Amalgams, and Model Choice; Response to Comments 327 $a5 Combining Risks from Several Tumors Using Markov Chain Monte Carlo6 Uncertainty in Dose Response from the Perspective of Microbial Risk; 7 Conclusions; Author Index; Subject Index 330 $aA valuable guide to understanding the problem of quantifying uncertainty in dose response relations for toxic substances In today's scientific research, there exists the need to address the topic of uncertainty as it pertains to dose response modeling. Uncertainty Modeling in Dose Response is the first book of its kind to implement and compare different methods for quantifying the uncertainty in the probability of response, as a function of dose. This volume gathers leading researchers in the field to properly address the issue while communicating concepts from diverse viewpoints and incorpo 410 0$aStatistics in Practice 606 $aEnvironmental toxicology$xMathematical models 606 $aToxicology$xDose-response relationship$xMathematical models 615 0$aEnvironmental toxicology$xMathematical models. 615 0$aToxicology$xDose-response relationship$xMathematical models. 676 $a615.9/02011 700 $aCooke$b Roger M.$f1946-$028435 701 $aCooke$b Roger M.$f1946-$028435 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143128803321 996 $aUncertainty modeling in dose response$91887902 997 $aUNINA