Statistics in Toxicology Using R - Couverture rigide

Hothorn, Ludwig A.

Couverture rigide

ISBN 10 : 1498701272 ISBN 13 : 9781498701273

Editeur : Chapman and Hall/CRC, 2016

Synopsis

The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysis of selected experimental data in toxicology and presents assay-specific suggestions, such as for the in vitro micronucleus assay.

Mostly focusing on hypothesis testing, the book covers standardized bioassays for chemicals, drugs, and environmental pollutants. It is organized according to selected toxicological assays, including:

• Short-term repeated toxicity studies
• Long-term carcinogenicity assays
• Studies on reproductive toxicity
• Mutagenicity assays
• Toxicokinetic studies

The book also discusses proof of safety (particularly in ecotoxicological assays), toxicogenomics, the analysis of interlaboratory studies and the modeling of dose-response relationships for risk assessment. For each toxicological problem, the author describes the statistics involved, matching data example, R code, and outcomes and their interpretation. This approach allows you to select a certain bioassay, identify the specific data structure, run the R code with the data example, understand the test outcome and interpretation, and replace the data set with your own data and run again. 

A propos du livre

À propos de l'auteur

Ludwig A. Hothorn is a professor in the Institute of Biostatistics at the Leibniz University of Hannover. Dr. Hothorn has published more than 130 papers in peer-reviewed journals and contributed numerous book chapters. His research interests include computational statistics using R as well as the application of statistical methods in biology, agriculture, medicine, life sciences, toxicology, pharmacology, and quantitative genetics.

À propos de la quatrième de couverture

The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysis of selected experimental data in toxicology and presents assay-specific suggestions, such as for the in vitro micronucleus assay. Mostly focusing on hypothesis testing, the book covers standardized bioassays for chemicals, drugs, and environmental pollutants. It is organized according to selected toxicological assays, including: Short-term repeated toxicity studies Long-term carcinogenicity assays Studies on reproductive toxicity Mutagenicity assays Toxicokinetic studies The book also discusses proof of safety (particularly in ecotoxicological assays), toxicogenomics, the analysis of interlaboratory studies and the modeling of dose-response relationships for risk assessment. For each toxicological problem, the author describes the statistics involved, matching data example, R code, and outcomes and their interpretation. This approach allows you to select a certain bioassay, identify the specific data structure, run the R code with the data example, understand the test outcome and interpretation, and replace the data set with your own data and run again.

Détails de l'édition

• Éditeur: Chapman and Hall/CRC
• Date d'édition: 2016
• Langue: anglais
• ISBN 10: 1498701272
• ISBN 13: 9781498701273
• Reliure: Relié
• Numéro d'édition: 1
• Nombre de pages: 234
• Coordonnées du fabricant: non disponible
• Personne responsable: gpsr@libri.de; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne