1st Edition

Statistics for Environmental Biology and Toxicology

By A. John Bailer, Walter. Piegorsch Copyright 1997
    596 Pages
    by Chapman & Hall

    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.

    Basic Probability and Statistical Distributions
    Introductory Concepts in Probability
    Families of Discrete Distributions
    Families of Continuous Distributions
    The Exponential Class
    Families of Multivariate Distributions
    Fundamentals of Statistical Inference
    Introductory Concepts in Statistical Estimation
    Nature and Properties of Estimators
    Techniques for Constructing Statistical Estimators
    Statistical Inference - Testing Hypotheses
    Statistical Inference - Confidence Intervals
    Confidence Intervals for Some Special Distributions
    Semi-Parametric Inference
    Fundamental Issues in Experiment Design
    Basic Terminology in Experiment Design
    The Experimental Unit
    Random Sampling and Randomization
    Sample Sizes and Optimal Animal Allocation
    Dose Selection
    Data Analysis of Treatment versus Control Differences
    Two-Sample Comparisons - Testing Hypotheses
    Two-Sample Comparisons - Confidence Intervals
    Treatment-versus-Control Multiple Comparisons
    Comparing More than Two Populations
    Multiple Comparisons via Bonferroni's Inequality
    Multiple Comparisons among a Control - Normal Sampling
    Multiple Comparisons among Binomial Populations
    Multiple Comparisons with a Control - Poisson Samling
    All-Pairwise Multiple Comparisons
    Trend Testing
    Simple Linear Regression for Normal Data
    William's Test for Normal Data
    Trend Tests for Proportions
    Cochran-Armitage Trend Test for Counts
    Overdispersed Discrete Data
    Distribution-Free Trend Testing
    Nonparametric Tests for Nonmonotone ("Umbrella") Trends
    Dose-Response Modeling and Analysis
    Dose-Response Models on a Continuous Scale
    Dose-Response Models on a Discrete Scale
    Potency Estimation for Dose-Response Data
    Comparing Dose-Response Curves
    Introduction to Generalized Linear Models
    Review of Classical Linear Models
    Generalizing the Classical Linear Model
    Generalized Linear Models
    Examples and Illustrations
    Analysis of Cross-Classified Tabular/Categorical Data
    RxC Contingency Tables
    Statistical Distributions for Categorical Data
    Statistical Tests of Independence in RxC Tables
    Log-Linear Models and Relationships to GLiMs
    Tables of Proportions
    Incorporating Historical Control Information
    Guidelines for Using Historical Control Data
    Two-Sample Hypothesis Testing - Normal Distribution Sampling
    Two-Sample Hypothesis Testing - Binomial Sampling
    Trend Testing with Historical Controls
    Survival Data Analysis
    Survival Data
    Lifetime Distributions
    Estimating the Survivor Function
    Nonparametric Methods for Comparing Survival Curves
    Regression Models for Survival Data


    Walter W. Piegorsch is Professor of Statistics at the University of South Carolina, Columbia, SC, USA. A. John Bailer is Professor of Mathematics and Statistics and Co-director of the Center for Environmental Toxicology and Statistics at Miami University, Oxford, OH, USA.

    "Teachers of statistics to students from other disciplines could will find this book useful, both for its condensed summaries of some of the more sophisticated techniques-in particular that for generalized linear models is helpful and also for the copious exercises and worked examples."
    -Short Book Reviews of the ISI
    "…I strongly recommend this text and believe it to be an excellent supplement for any biostatistics course or courses in related disciplines."
    -Australian & New Zealand Journal of Statistics
    "This book is an excellent source for information about the relevant statistical methods with a strong emphasis on applications. This is one of the best books that I have seen recently."
    -Technometrics, Vol. 40, No.3

    "The many examples are well selected and illustrate the use of the methods introduced on relevant data."… the book introduces many statistical concepts, it is concise but careful and it has many good examples…. could be used as a basic statistical textbook for researchers in environmental biology."
    -Statistics in Medicine, Vol. 20: 1143-1152, 2001