Dose-response analysis using R
Author(s)
Bibliographic Information
Dose-response analysis using R
(The R series)(A Chapman & Hall book)
CRC Press, 2021
- : pbk
Available at 1 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Other authors: Signe Marie Jensen, Daniel Gerhard, Jens Carl Streibig
Includes bibliographical references (p. 199-210) and index
Description and Table of Contents
Description
Nowadays the term dose-response is used in many different contexts and many different scientific disciplines including agriculture, biochemistry, chemistry, environmental sciences, genetics, pharmacology, plant sciences, toxicology, and zoology.
In the 1940 and 1950s, dose-response analysis was intimately linked to evaluation of toxicity in terms of binary responses, such as immobility and mortality, with a limited number of doses of a toxic compound being compared to a control group (dose 0). Later, dose-response analysis has been extended to other types of data and to more complex experimental designs. Moreover, estimation of model parameters has undergone a dramatic change, from struggling with cumbersome manual operations and transformations with pen and paper to rapid calculations on any laptop. Advances in statistical software have fueled this development.
Key Features:
Provides a practical and comprehensive overview of dose-response analysis.
Includes numerous real data examples to illustrate the methodology.
R code is integrated into the text to give guidance on applying the methods.
Written with minimal mathematics to be suitable for practitioners.
Includes code and datasets on the book's GitHub: https://github.com/DoseResponse.
This book focuses on estimation and interpretation of entirely parametric nonlinear dose-response models using the powerful statistical environment R. Specifically, this book introduces dose-response analysis of continuous, binomial, count, multinomial, and event-time dose-response data. The statistical models used are partly special cases, partly extensions of nonlinear regression models, generalized linear and nonlinear regression models, and nonlinear mixed-effects models (for hierarchical dose-response data). Both simple and complex dose-response experiments will be analyzed.
Table of Contents
Introduction
Dose-response models
Estimation procedures
Model selection and model averaging
Model diagnostics and how to fix violations
Inverse regression
Simultaneous inference
Grouped data
Nonlinear mixed effects models
Design of experiments
Appendix
by "Nielsen BookData"