Models for Discrete Data
by Daniel Zelterman
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.
Also Recommended: Categorical Data Analysis Using the SAS System; Survival Analysis Using the SAS System: A Practical Guide; Logistic Regression Using the SAS System: Theory and Application; SAS System for Mixed Models; SAS/STAT User's Guide, Version 6, Fourth Edition, Volumes 1 and 2; SAS/STAT Software: Changes and Enhancements through Release 6.12; Univariate and Multivariate General Linear Models: Theory and Applications Using SAS Software; A Step-by-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling; Applied Multivariate Statistics with SAS Software, Second Edition;
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