Dose-Response Analysis Using R

Christian Ritz

ISBN 10: 1032091819 / ISBN 13: 9781032091815

Editore: Chapman And Hall/CRC Jun 2021, 2021

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This item is printed on demand - it takes 3-4 days longer - Neuware 226 pp. Englisch.

Codice articolo 9781032091815

Dati bibliografici

• Titolo: Dose-Response Analysis Using R
• Editore: Chapman And Hall/CRC Jun 2021
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 1032091819
• ISBN 13: 9781032091815
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 234 L x 156 A x 12 P (millimetri) 234 millimetri di larghezza per 156 millimetri di altezza per 12 millimetri di profondità
• Peso: 351 grammi

Descrizione articolo

Riassunto

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.

Informazioni sull?autore

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.