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Book Summary
Multiway Contingency Tables Analysis by Thomas D. Wickens is a rigorous graduate-level statistics textbook covering log-linear models for multidimensional categorical data. It explains model specification, estimation, and interpretation, with practical examples. Ideal for researchers and students who need to analyze complex contingency tables beyond simple two-way chi-square tests.
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About Multiway Contingency Tables Analysi...
This advanced textbook provides a comprehensive treatment of log-linear models for multiway contingency tables. Wickens guides readers from basic principles of categorical data through model specification, parameter estimation, and hypothesis testing. The book emphasizes the interpretation of complex interactions and the assessment of model fit, using real-world examples from the social and behavioral sciences. It covers hierarchical models, maximum likelihood estimation, and strategies for selecting among competing models. While mathematically rigorous, the text balances theory with practical application, making it a valuable resource for graduate students and researchers who need to analyze multidimensional categorical data. It assumes familiarity with basic statistics and matrix algebra, positioning it as a bridge between introductory categorical data analysis and advanced multivariate methods.
Who should read Multiway Contingency Tables Analysi...?
Graduate students and researchers in statistics, social sciences, and public health who analyze categorical data. It suits those who already understand two-way contingency tables and want to master log-linear modeling for three-way and higher-dimensional tables. Quantitative analysts in survey research, epidemiology, and psychology will benefit from its practical guidance on model interpretation and selection. Instructors teaching advanced categorical data analysis courses will find it a solid reference.
Pros & Cons
Pros
- ✓ Rigorous and thorough coverage of log-linear models for multiway tables
- ✓ Clear explanations of model specification, estimation, and interpretation
- ✓ Practical examples from social and behavioral sciences
- ✓ Balances mathematical theory with applied guidance
- ✓ Useful for both self-study and graduate coursework
Cons
- ✗ Assumes prior knowledge of matrix algebra and basic statistics
- ✗ Not suitable for beginners in categorical data analysis
- ✗ Limited coverage of modern software implementations
- ✗ Some sections are dense and require careful reading
- ✗ Examples may feel dated to some readers
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Frequently asked questions
Is this book suitable for beginners in statistics?
No, it assumes a solid foundation in basic statistics and matrix algebra. It is intended for graduate students and researchers already familiar with two-way contingency tables.
Does the book include software examples?
The focus is on statistical theory and interpretation rather than software. Some examples may reference software, but it is not a software manual.
What types of data does the book cover?
It covers multiway contingency tables, which involve three or more categorical variables. The methods are applicable to survey data, experimental data, and observational studies.
Is this book useful for social science research?
Yes, it includes examples from the social and behavioral sciences and is widely used by researchers in psychology, sociology, and education.
Does it cover model selection and fit assessment?
Yes, it provides detailed guidance on comparing models, assessing fit, and interpreting parameters in complex tables.
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