Dose-Response Analysis Using R: 1st Edition (Hardback) book cover

Dose-Response Analysis Using R

1st Edition

By Christian Ritz, Signe Marie Jensen, Daniel Gerhard, Jens Carl Streibig

Chapman and Hall/CRC

214 pages | 47 B/W Illus.

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Hardback: 9781138034310
pub: 2019-07-17
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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:

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

Continuous data

Binary and binomial dose-response data

Count dose-response data

Multinomial dose-response data

Time-to-event-response data

Benchmark dose estimation

Hierarchical nonlinear models

Appendix A: Estimation

Appendix B: Dose-response model functions

Appendix C: More R Code

Bibliography, Index

About the Authors

Christian Ritz is an Associate Professor at the University of Copenhagen, Denmark.

Signe M. Jensen is an Assistant Professor at the University of Copenhagen, Denmark.

Daniel Gerhard is a Senior Lecturer at the University of Caterbury, New Zealand.

Jens Carl Streibig is Professor Emeritus at the University of Copenhagen, Denmark.

About the Series

Chapman & Hall/CRC The R Series

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Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
MEDICAL / Toxicology