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.
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- Ralf Schafer, University Koblenz-Landau
"Analysis of dose-response curves is one of the critical ways used to assess the effect of a toxicant (or other treatments) on plant growth. I have done many such analyses using the drc module in R developed by the authors of Dose-Response Analysis Using R. This new book is a wonderful new compendium of methodologies illustrated with relevant examples to conduct such analyses properly. A 'Must Have' resource for anyone relying on dose-response analysis in their work."
-Franck E. Dayan, Agricultural Biology Department, Colorado State University
"This book will be useful to both applied statisticians and a wide range of biologists. It combines a text on statistical modeling of dose-response data with lots of examples of using R and the drc package for data analysis. Appendix B, describing models for dose-response data, is an extremely useful and thorough overview of the huge number of possible models. It contains cross-references between equivalent models and a wealth of literature citations from diverse fields. This alone is worth the price of the book. The examples are drawn from the published literature. They provide a nice range of complexity, starting with simple introductions and finishing with quite complex analyses."
- Philip Dixon, Iowa State University