Items related to Models for Discrete Data

Models for Discrete Data - Hardcover

Zelterman, Daniel

 
9780198524366: Models for Discrete Data

Synopsis

Discrete or count data arise in experiments where the outcomes are countable and classified into unique, non-overlapping categories. This book describes the statistical models for evaluating such data. It provides an introduction for graduate students and a concise review for practitioners. The book provides the first in-depth coverage of a number of topics, including the negative multinormal distribution, the many forms of hypergeometric distribution, and coordinate-free models. A detailed treatment of the issues of sample size and power are given in terms of exact inference and asymptotic, non-central chi-squared approximations. Throughout the text, the author interweaves standard statistical software, particularly SAS, with practical examples and current theory.

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About the Author


Daniel Zelterman is Professor of Biostatistics in the Yale School of Public Health and Director of the Biostatistics Core of the Yale Comprehensive Cancer Center. He previously held academic positions at the University of Minnesota and at the State University of New York at Albany. He is an elected Fellow of the American Statistical Association. He is an Associate Editor of Biometrics and several other statistical journals.

Review


"Its level is suitable for graduate courses in statistics and biostatistics departments and the examples given have a decidedly health/medical bias. It is noteworthy that throughout the book, the software in integrated into the text."-- Quarterly of Applied Mathematics


"This book does a nice job of blending the theory and applications and is suitable for a one-semester graduate-level course. It is also a useful book for practitioners, especially in health and medical sciences." -- Technometrics, Aug 2000, Vol 42, No 3


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