Uncertainty Modeling in Dose Response: Bench Testing Environmental Toxicity / Edition 1

Hardcover (Print)
Buy New
Buy New from BN.com
$109.42
Used and New from Other Sellers
Used and New from Other Sellers
from $104.69
Usually ships in 1-2 business days
(Save 20%)
Other sellers (Hardcover)
  • All (7) from $104.69   
  • New (6) from $104.69   
  • Used (1) from $109.41   

Overview

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.

Read More Show Less

Product Details

  • ISBN-13: 9780470447505
  • Publisher: Wiley
  • Publication date: 7/7/2009
  • Series: Statistics in Practice Series , #74
  • Edition number: 1
  • Pages: 230
  • Product dimensions: 6.40 (w) x 9.30 (h) x 0.70 (d)

Meet the Author

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.

Read More Show Less

Table of Contents

Acknowledgments.

Contributors.

Introduction (Roger M. Cooke and Margaret MacDonell).

1 Analysis of Dose–Response Uncertainty Using Benchmark Dose Modeling (Jeff Swartout).

Comment: The Math/Stats Perspective on Chapter 1: Hard Problems Remain (Allan H. Marcus).

Comment: EPI/TOX Perspective on Chapter 1: Re-formulating the Issues (Jouni T. Tuomisto).

Comment: Regulatory/Risk Perspective on Chapter 1: A Good Baseline (Weihsueh Chiu).

Comment: A Question Dangles (David Bussard).

Comment: Statistical Test for Statistics-as-Usual Confidence Bands (Roger M. Cooke).

Response to Comments (Jeff Swartout).

2 Uncertainty Quantification for Dose–Response Models Using Probabilistic Inversion with Isotonic Regression: Bench Test Results (Roger M. Cooke).

Comment: Math/Stats Perspective on Chapter 2: Agreement and Disagreement (Thomas A. Louis).

Comment: EPI/TOX Perspective on Chapter 2: What Data Sets Per se Say (Lorenz Rhomberg).

Comment: Regulatory/Risk Perspective on Chapter 2: Substantial Advances Nourish Hope for Clarity? (Rob Goble).

Comment: A Weakness in the Approach? (Jouni T. Tuomisto).

Response to Comments (Roger Cooke).

3 Uncertainty Modeling in Dose Response Using Nonparametric Bayes: Bench Test Results (Lidia Burzala and Thomas A. Mazzuchi).

Comment: Math/Stats Perspective on Chapter 3: Nonparametric Bayes (Roger M. Cooke).

Comment: EPI/TOX View on Nonparametric Bayes: Dosing Precision (Chao W. Chen).

Comment: Regulator/Risk Perspective on Chapter 3: Failure to Communicate (Dale Hattis).

Response to Comments (Lidia Burzala).

4 Quantifying Dose–Response Uncertainty Using Bayesian Model Averaging (Melissa Whitney and Louise Ryan).

Comment: Math/Stats Perspective on Chapter 4: Bayesian Model Averaging (Michael Messner).

Comment: EPI/TOX Perspective on Chapter 4: Use of Bayesian Model Averaging for Addressing Uncertainties in Cancer Dose–Response Modeling (Margaret Chu).

Comment: Regulatorary/Risk Perspective on Chapter 4: Model Averages, Model Amalgams, and Model Choice (Adam M. Finkel).

Response to Comments (Melissa Whitney and Louise Ryan).

5 Combining Risks from Several Tumors Using Markov Chain Monte Carlo (Leonid Kopylev, John Fox, and Chao Chen).

6 Uncertainty in Dose Response from the Perspective of Microbial Risk (P. F. M. Teunis).

7 Conclusions (David Bussard, Peter Preuss, and Paul White).

Author Index.

Subject Index.

Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(0)

1 Star

(0)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)