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OverviewFull Product DetailsAuthor: A.John Bailer , Walter. Piegorsch (University of Arizona, Tucson, USA) , Walter. Piegorsch (University of Arizona, Tucson, USA) , Niels Keiding (University of Copenhagen, Denmark)Publisher: Chapman and Hall Imprint: Chapman and Hall Volume: 4 Dimensions: Width: 21.00cm , Height: 3.20cm , Length: 28.00cm Weight: 0.879kg ISBN: 9780412047312ISBN 10: 0412047314 Pages: 596 Publication Date: 01 July 1997 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents"Basic Probability and Statistical Distributions Introductory Concepts in Probability Families of Discrete Distributions Families of Continuous Distributions The Exponential Class Families of Multivariate Distributions Summary Exercises 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 Summary Exercises 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 Summary Exercises Data Analysis of Treatment versus Control Differences Two-Sample Comparisons - Testing Hypotheses Two-Sample Comparisons - Confidence Intervals Summary Exercises 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 Summary Exercises 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 Summary Exercises 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 Summary Exercises Introduction to Generalized Linear Models (GLiMs) Review of Classical Linear Models Generalizing the Classical Linear Model Generalized Linear Models Examples and Illustrations Summary Exercises 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 Summary Exercises 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 Summary Exercises Survival Data Analysis Survival Data Lifetime Distributions Estimating the Survivor Function Nonparametric Methods for Comparing Survival Curves Regression Models for Survival Data Summary Exercises Appendices References"ReviewsTeachers 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 Author InformationWalter 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. Tab Content 6Author Website:Countries AvailableAll regions |
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