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Modelling Frequency and Count Data


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Table of Contents

1: One-way frequency tables
2: Larger tables
3: Regression models
4: Ordinal variables
5: Zero frequencies
6: Fitting distributions
7: Counting processes
8: Markov chains
9: Structured transition matrices
10: Overdispersion and cluster models
11: GLIM macros


"Modelling frequency and count data is an excellent text for a master's level course in applied statistics or as a reference for any applied statistician. An introductory statistics course and some knowledge of log-linear and logistic regression models is [sic] assumed. Theoretical details are kept to a minimum but underlying concepts are clearly demonstrated. This text provides a brief, but broad, introduction to a wide variety of models. Every model is introduced by a real data example . . . and followed through from beginning to end in terms of both analysis and model evaluation; an attraction for both students and applied statisticians working on real world problems. . . . In summary, I would recommend this text strongly to any statistician doing applied work as well as a text for a course in categorical data analysis. It is both a comprehensive and practical survey of models for frequency and count data."--Statistical Methods in Medical Research

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