Categorical data analysis /
"A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, lo...
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| Format: | Book |
| Language: | English |
| Published: |
Hoboken, N.J. :
Wiley,
[2013]
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| Edition: | Third edition. |
| Series: | Wiley series in probability and statistics.
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| Subjects: |
Table of Contents:
- Introduction: Distributions and inference for categorical data
- Describing contingency tables
- Inference for two-way contingency tables
- Introduction to generalized linear models
- Logistic regression
- Building, checking, and applying logistic regression models
- Alternative modeling of binary response data
- Models for multinomial responses
- Loglinear models for contingency tables
- Building and extending loglinear models
- Models for matched pairs
- Clustered categorical data: marginal and transitional models
- Clustered categorical data: random effects models
- Other mixture models for discrete data
- Non-model-based classification and clustering
- Large- and small-sample theory for multinomial models
- Historical tour of categorical data analysis
- Appendix A: Statistical software for categorical data analysis
- Appendix B: Chi-squared distribution values.