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eBook Analysis of Ordinal Categorical Data epub

by Alan Agresti

eBook Analysis of Ordinal Categorical Data epub
  • ISBN: 0470082895
  • Author: Alan Agresti
  • Genre: Science
  • Subcategory: Mathematics
  • Language: English
  • Publisher: Wiley; 2 edition (April 19, 2010)
  • Pages: 424 pages
  • ePUB size: 1911 kb
  • FB2 size 1883 kb
  • Formats rtf azw lit mobi


Agresti, Alan An introduction to categorical data analysis, Alan Agresti. Variable Distinction, 2 Nominal/Ordinal Scale Distinction, 2 Organization of this Book, 3.

Agresti, Alan An introduction to categorical data analysis, Alan Agresti. p. cm. Includes bibliographical references and index. ISBN 978-0-471-22618-5. Probability Distributions for Categorical Data, 3. . 1 Binomial Distribution, 4 . 2 Multinomial Distribution, 5.

Agresti pretty much founded the field of categorical analysis (from what I understand), and this book lays out the foundations of ordinal categorical analysis. It's loaded with real-world examples, from politic leanings to public opinions on everything from abortion to astrology, right on down to the diet of alligators.

addressed in his books Categorical Data Analysis (Agresti, 2002) and An Introduction. to Categorical Data Analysis (Agresti, 2007), and focuses on more advanced topics

addressed in his books Categorical Data Analysis (Agresti, 2002) and An Introduction. to Categorical Data Analysis (Agresti, 2007), and focuses on more advanced topics. New material includes chapters on marginal models and random effects models for. clustered data (Chapters 9 and 10) and Bayesian methods (Chapter 11).

Agresti - Categorical data analysis. 732 Pages · 2002 · . 3 MB · 1,061 Downloads ·English. We can't help everyone, but everyone can help someone. When the Moon Split: A biography of Prophet Muhammad. 57 MB·64,666 Downloads.

Introduction to Categorical Data Analysis Procedures. Contents Agresti, A. (1984), Analysis of Ordinal Categorical Data, New York: John Wiley & Sons. Overview: Categorical Data Analysis Procedures . Categorical data result from observations on multiple subjects where one or more categorical variables are observed for each subject. If there is only one categorical variable, then the data are generally represented by a frequency table, which lists each observed value of the variable and its frequency of occurrence. Agresti, A.

Скачать бесплатно книгу Categorical Data Analysis - Alan Agresti в форматах fb2 . Analysis of Ordinal Categorical Data. Foundations of Linear and Generalized Linear Models.

Скачать бесплатно книгу Categorical Data Analysis - Alan Agresti в форматах fb2, rtf, epub, pdf, txt или читать онлайн. Отзывы на книгу, похожие книги на Categorical Data Analysis. Statistics in Medicine It is a total delight reading this book.

Categorical Data Analysis.

Categorical Data Analysis was among those chosen. Prescriptions for how ordinal variables should be treated differently than nominal variables. Discussion of exact small-sample procedures. The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences.

Statistical science’s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy. Analysis of Ordinal Categorical Data, Second Edition provides an introduction to basic descriptive and inferential methods for categorical data, giving thorough coverage of new developments and recent methods. Special emphasis is placed on interpretation and application of methods including an integrated comparison of the available strategies for analyzing ordinal data. Practitioners of statistics in government, industry (particularly pharmaceutical), and academia will want this new edition.
Comments: (4)
Xwnaydan
Agresti pretty much founded the field of categorical analysis (from what I understand), and this book lays out the foundations of ordinal categorical analysis. It's loaded with real-world examples, from politic leanings to public opinions on everything from abortion to astrology, right on down to the diet of alligators. If you can put a semi-quantitative scale to it (in other words, if you can rank them and say "this is worse than that, this is better than that", then this book will help you understand it.

This was my introduction to the field, and I found it quite accessible, at least in the early chapters (haven't gotten all the way through). You can find stuff for free on the web, but none of them will give you the context like a book such as this, explaining the history, the notational conventions, the reasons why you need to do logistic regression in the first (rather than linear regression), and rounding it out with chapters on how to bring in random-effects (hierarchical) models and Bayesian inference.

Other books focus heavily on how to implement these models in various languages, like S-PLUS and R, and they have their place. But I like to start a new area with the conceptual framework, and this book does a good job of laying that out.
Tat
I'm an Institutional Research Analyst working for a University analyzing educational data, or GRADES, to be precise. This book has been very helpful for my work and quite straight forward to use. I found some R code online to implement the models and had at it.

This text would likely be easy to use for an advanced undegraduate course, or a M.Sc level course. And for a practitioner with a good statistical background (I'm finishing up a M.Sc in Stats) it is easy to follow. I'm not sure it would be the right book for a practitioner in another field, but the author goes to great lengths to explain what's going on with the models as well, so maybe. 5 stars for me!
Brightfury
Professor Agresti never lets us down. I'd highly recommend this book to statisticians and quantitative researchers.
porosh
such a needed resource for my masters -
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