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Purposefully designed as a resource for practicing and student toxicologists, Statistics and Experimental Design for Toxicologists and Pharmacologists, Fourth Edition equips you for the regular statistical analysis of experimental data. Starting with the assumption of basic mathematical skills and knowledge, the author supplies a complete and systematic yet practical introduction to the statistical methodologists available for, and used in, the discipline. For every technique presented, a worked example from toxicology is also presented. See what's new in the Fourth Edition: The first practical guide to performing meta analysis allowing for using the power inherent in multiple similar studies Coverage of Bayesian analysis and data analysis in pharmacology and toxicology Almost 200 problems with solutions Discussion of analysis of receptor binding assays, safety pharmacology assays and other standard types conducted in pharmacology A new chapter explaining the basics of Good Laboratory Practices (GLPs) For those with computer skills, this edition has been enhanced with the addition of basic SAS Written specifically for toxicologists and pharmacologists, the author draws on more than 30 years of experience to provide understanding of the philosophical underpinnings for the overall structure of analysis. The book's organization fosters the ordered development of skills and yet still facilitates ease of access to information as needed. This Fourth Edition gives you the tools necessary to perform rigorous and critical analysis of experimental data and the insight to know when to use them.
"This Fourth Edition provides tools for the rigorous and critical analysis of experimental data. Assuming only basic mathematical skills, the book provides a complete and exhaustive introduction to the statistical methods available and updates all material to cover current practices. The book also provides three entirely new and up-to-the-minute chapters. One provides the first practical guide to performing meta analysis allowing for using the power inherent in multiple similar studies; two others cover Bayesian analysis and data analysis in pharmacology, which discuss analysis of receptor binding assays, safety pharmacology assays, and other standard study types conducted in pharmacology."--Publisher's description.
This book serves as a primary text for students of pharmacology, toxicology, and biology, and as a practical handbook to support the daily operations of the toxicology laboratory and researcher. This edition retains the structure of earlier editions, but has been extensively revised to provide both the student and the working toxicologist with the necessary tools for the rigorous and critical design of studies and analysis of experimental data. Assuming only basic mathematical skills as a starting point, Statistics and Experimental Design for Toxicologists provides a thorough and exhaustive introduction to the statistical methods available to and used in the discipline. A worked, practical example from the field is provided for each technique presented. Written from a toxicologist's perspective, this book provides both the methodological tools necessary to analyze experimental toxicology data and the insight to know when to use them.
Statistics and Experimental Design for Toxicologists has been designed as both a sourcebook for the practicing toxicologist and a textbook for the student toxicologist. Its function is to provide both with tools for the rigorous and critical analysis of experimental data. Assuming only basic mathematical skills, the volume provides a complete and exhaustive introduction to the statistical methods available to and used in the discipline. For each technique presented, a practical example is provided and a collection of problems is also included, together with appendices containing the necessary tables of test values.
Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences A practical guide to the use of basic principles of experimental design and statistical analysis in pharmacology Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences provides clear instructions on applying statistical analysis techniques to pharmacological data. Written by an experimental pharmacologist with decades of experience teaching statistics and designing preclinical experiments, this reader-friendly volume explains the variety of statistical tests that researchers require to analyze data and draw correct conclusions. Detailed, yet accessible, chapters explain how to determine the appropriate statistical tool for a particular type of data, run the statistical test, and analyze and interpret the results. By first introducing basic principles of experimental design and statistical analysis, the author then guides readers through descriptive and inferential statistics, analysis of variance, correlation and regression analysis, general linear modelling, and more. Lastly, throughout the textbook are numerous examples from molecular, cellular, in vitro, and in vivo pharmacology which highlight the importance of rigorous statistical analysis in real-world pharmacological and biomedical research. This textbook also: Describes the rigorous statistical approach needed for publication in scientific journals Covers a wide range of statistical concepts and methods, such as standard normal distribution, data confidence intervals, and post hoc and a priori analysis Discusses practical aspects of data collection, identification, and presentation Features images of the output from common statistical packages, including GraphPad Prism, Invivo Stat, MiniTab and SPSS Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences is an invaluable reference and guide for undergraduate and graduate students, post-doctoral researchers, and lecturers in pharmacology and allied subjects in the life sciences.
Statistics plays an important role in pharmacology and related subjects such as toxicology and drug discovery and development. Improper statistical tool selection for analyzing the data obtained from studies may result in wrongful interpretation of the performance or safety of drugs. This book communicates statistical tools in simple language. The
A Comprehensive Guide to Toxicology in Nonclinical Drug Development, Third Edition is a valuable reference providing a complete understanding of all aspects of nonclinical toxicology in pharmaceutical research. This updated edition has been expanded and re-developed covering a wide-range of toxicological issues in small molecules and biologics. Topics include ADME in drug discovery, pharmacokinetics, toxicokinetics, formulations, and genetic toxicology testing. The book has been thoroughly updated throughout to reflect the latest scientific advances and includes new information on antiviral drugs, anti-diabetic drugs, immunotherapy, and a discussion on post-pandemic drug development challenges and opportunities. This is an essential and practical resource for all toxicologists involved in nonclinical testing in industry, academic, and regulatory settings. Provides updated, unique content not covered in one comprehensive resource, including chapters on stem cells, antiviral drugs, anti-diabetic drugs, and immunotherapy Includes the latest international guidelines for nonclinical toxicology in both small and large molecules Incorporates practical examples in order to illustrate day-to-day activities and expectations associated with working in nonclinical toxicology
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
A guide to the issues relevant to the design, analysis, and interpretation of toxicity studies that examine chemicals for use in the environment Statistical Analysis of Ecotoxicity Studies offers a guide to the design, analysis, and interpretation of a range of experiments that are used to assess the toxicity of chemicals. While the book highlights ecotoxicity studies, the methods presented are applicable to the broad range of toxicity studies. The text contains myriad datasets (from laboratory and field research) that clearly illustrate the book's topics. The datasets reveal the techniques, pitfalls, and precautions derived from these studies. The text includes information on recently developed methods for the analysis of severity scores and other ordered responses, as well as extensive power studies of competing tests and computer simulation studies of regression models that offer an understanding of the sensitivity (or lack thereof) of various methods and the quality of parameter estimates from regression models. The authors also discuss the regulatory process indicating how test guidelines are developed and review the statistical methodology in current or pending OECD and USEPA ecotoxicity guidelines. This important guide: Offers the information needed for the design and analysis to a wide array of ecotoxicity experiments and to the development of international test guidelines used to assess the toxicity of chemicals Contains a thorough examination of the statistical issues that arise in toxicity studies, especially ecotoxicity Includes an introduction to toxicity experiments and statistical analysis basics Includes programs in R and excel Covers the analysis of continuous and Quantal data, analysis of data as well as Regulatory Issues Presents additional topics (Mesocosm and Microplate experiments, mixtures of chemicals, benchmark dose models, and limit tests) as well as software Written for directors, scientists, regulators, and technicians, Statistical Analysis of Ecotoxicity Studies provides a sound understanding of the technical and practical issues in designing, analyzing, and interpreting toxicity studies to support or challenge chemicals for use in the environment.