This book explains how the computer programs work and why and when they can be applied to problems in toxicology. It discusses the statistical models used and their applications in a general fashion. The book overviews the problems that can arise from the blind use of the statistical models.

This book explains how the computer programs work and why and when they can be applied to problems in toxicology. It discusses the statistical models used and their applications in a general fashion. The book overviews the problems that can arise from the blind use of the statistical models.

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

Statistics for Environmental Biology and Toxicology presents and illustrates statistical methods appropriate for the analysis of environmental data obtained in biological or toxicological experiments. Beginning with basic probability and statistical inferences, this text progresses through non-linear and generalized linear models, trend testing, time-to-event data and analysis of cross-classified tabular and categorical data. For the more complex analyses, extensive examples including SAS and S-PLUS programming code are provided to assist the reader when implementing the methods in practice.

This collection of papers on aspects of statistics in toxicology is will be of interest to all medical statisticians. It offers findings from numerous leading experts from around the world including A. Whitehead and R. N. Connor (University of Reading), L. Ryan (Harvard), A. P. Grieve (Pfizer Research), K.J. Risko (Northern Telecom), and B.H. Margolin (University of North Carolina). This is the latest in the popular Royal Statistical Society Lecture Series, and will be essential reading for all those involved in this area.

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.

A comprehensive overview of techniques and systems currently utilized in predictive toxicology, this reference presents an in-depth survey of strategies, algorithms, and prediction methods to select, calculate, and represent the features and properties of chemical structures in biological systems. It provides sources of high-quality toxicity data, the most important commercial and noncommercial predictive toxicology programs, and advanced technologies in computational chemistry, biology, statistics, and data mining. Predictive Toxicology explores applications that go beyond classical structure-activity relationships and discusses programs such as OncoLogic, META, MC4PC, PASS, and lazar.

The Nature and Use of Ecotoxicological Evidence: Natural Science, Statistics, Psychology, and Sociology examines how toxicologists and environmental professionals come to understand and make decisions about possible harm from pollutants. Drawing on concepts and techniques from the natural, social and mathematical sciences, the book emphasizes how pollutant-related evidence is gathered, assessed, communicated and applied in decision-making. Each chapter begins with a real-world example before exploring fundamental cognitive, social, statistical or natural science concepts to explain the opening example. Methods from other disciplines for recognizing, reducing or removing the influence of impediments in wise decision-making are highlighted in each chapter. Misreading evidence by the scientific community, and miscommunication to regulators and the public, remain major impediments to wise action in pollution issues. Which evidence comes to dominate the dialogue among scientists, regulators and decision makers depends on social and scientific dynamics. Yet psychological and sociological factors that influence the movement of evidence through scientific communities to regulators receive cursory discussion by professionals unfamiliar with the sociology literature. Toxicologists, environmental scientists, psychologists and professionals and students across the sciences will find the book useful for understanding how evidence is generated, assessed and communicated in their own fields. - Includes groundbreaking research synthesizing information from across the sciences to understand the decision-making process - Provides real life examples and uses theoretical concepts to analyze them in clear, direct language - Encourages critical thinking about complex problems

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