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 analysi
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 analysi
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.
Inhaltsangabe
Principles. Simultaneous comparisons versus a negative control. Evaluation of long-term carcinogenicity assays. Evaluation of mutagenicity assays. Evaluation of reproductive toxicity assays. Ecotoxicology: Test on significant toxicity. Modeling of dose-response relationships. Further methods. Conclusions. Appendix.
Principles. Simultaneous comparisons versus a negative control. Evaluation of long-term carcinogenicity assays. Evaluation of mutagenicity assays. Evaluation of reproductive toxicity assays. Ecotoxicology: Test on significant toxicity. Modeling of dose-response relationships. Further methods. Conclusions. Appendix.
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