Modelling Frequency and Count Data

• Many practical examples and exercises
• Suitable for many major statistical packages
• Demonstrates unifying role of categorical data underlying modern statistics
• Makes the important distinction between frequencies of independent events and counts of repeated data

Readership: Third year undergraduates in statistics, postgraduates, applied statisticians, research workers with a knowledge of statistics.

J. K. Lindsey, Professor of Biostatistics, Limburgs University; Professor of Quantitative Methodology, University of Liege, Belgium

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
Bibliography
Index