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Contingency Table Analysis: Methods and Implementation Using R Softcover Repri Edition
Contributor(s): Kateri, Maria (Author)
ISBN: 1493939599     ISBN-13: 9781493939596
Publisher: Birkhauser
OUR PRICE:   $52.24  
Product Type: Paperback - Other Formats
Published: September 2016
Qty:
Additional Information
BISAC Categories:
- Mathematics | Applied
- Mathematics | Probability & Statistics - General
- Social Science | Statistics
Dewey: 519.53
Series: Statistics for Industry and Technology
Physical Information: 0.68" H x 6.14" W x 9.21" (1.00 lbs) 304 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

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.

Special features and topics include:

* A characteristic motivating example for each topic covered

* Review of classical and recent methodology for analysis of contingency tables

* Emphasis on applications and methods of fitting models using standard statistical tools - such as SPSS, R, and BUGS - and on interpretation of the results

* Elaborated account of association and symmetry models

* Focus on treatment of ordinal variables

* Detailed insight into exact and Bayesian inference

* Presentation of selected advanced topics, including a discussion of the related literature and links to corresponding algorithms

* Up-to-date supplementary material available on the author's website

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.