Contingency Table Analysis: Methods and Implementation Using R
โ Scribed by Maria Kateri (auth.)
- Publisher
- Birkhรคuser Basel
- Year
- 2014
- Tongue
- English
- Leaves
- 315
- Series
- Statistics for Industry and Technology
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Contingency tables arise in diverse fields, including life sciences, education, social and political sciences, notably market research and opinion surveys. Their analysis plays an essential role in gaining insight into structures of the quantities under consideration and in supporting decision making.
Combining both theory and applications, this book presents models and methods for the analysis of two- and multidimensional-contingency tables. The author uses a threefold approach, presenting fundamental models and related inference, highlighting their interpretational aspects, and demonstrating their practical usefulness. Emphasis is on applications and methods of fitting models using standard statistical tools - such as SPSS, R, and BUGS - and on interpretation of the results.
An excellent reference for advanced undergraduates, graduate students, and practitioners in statistics as well as biosciences, social sciences, education, and economics, the work may also be used as a textbook for a course on categorical data analysis. Prerequisites include basic background on statistical inference and knowledge of statistical software packages.
โฆ Table of Contents
Front Matter....Pages i-xvii
Introduction....Pages 1-15
Analysis of Two-way Tables....Pages 17-61
Analysis of Multi-way Tables....Pages 63-83
Log-Linear Models....Pages 85-124
Generalized Linear Models and Extensions....Pages 125-152
Association Models....Pages 153-196
More on Association Models and Related Methods....Pages 197-213
Response Variable Analysis in Contingency Tables....Pages 215-231
Analysis of Square Tables....Pages 233-259
Further Topics....Pages 261-269
Back Matter....Pages 271-304
โฆ Subjects
Statistical Theory and Methods; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law; Statistics for Life Sciences, Medicine, Health Sciences; Statistics and Computing/Statistics Programs; Applications of M
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