Lectures on Categorical Data Analysis

  • Tamás  Rudas

Part of the Springer Texts in Statistics book series (STS)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Tamás Rudas
    Pages 1-18
  3. Tamás Rudas
    Pages 19-40
  4. Tamás Rudas
    Pages 41-56
  5. Tamás Rudas
    Pages 57-82
  6. Tamás Rudas
    Pages 83-108
  7. Tamás Rudas
    Pages 109-136
  8. Tamás Rudas
    Pages 137-155
  9. Tamás Rudas
    Pages 157-182
  10. Tamás Rudas
    Pages 183-196
  11. Tamás Rudas
    Pages 197-223
  12. Tamás Rudas
    Pages 225-253
  13. Tamás Rudas
    Pages 255-266
  14. Tamás Rudas
    Pages 267-275
  15. Back Matter
    Pages 277-285

About this book

Introduction

This book offers a relatively self-contained presentation of the fundamental results in categorical data analysis, which plays a central role among the statistical techniques applied in the social, political and behavioral sciences, as well as in marketing and medical and biological research. The methods applied are mainly aimed at understanding the structure of associations among variables and the effects of other variables on these interactions.  A great advantage of studying categorical data analysis is that many concepts in statistics become transparent when discussed in a categorical data context, and, in many places, the book takes this opportunity to comment on general principles and methods in statistics, addressing not only the “how” but also the “why.”

Assuming minimal background in calculus, linear algebra, probability theory and statistics, the book is designed to be used in upper-undergraduate and graduate-level courses in the field and in more general statistical methodology courses, as well as a self-study resource for researchers and professionals. The book covers such key issues as: higher order interactions among categorical variables; the use of the delta-method to correctly determine asymptotic standard errors for complex quantities reported in surveys; the fundamentals of the main theories of causal analysis based on observational data; the usefulness of the odds ratio as a measure of association; and a detailed discussion of log-linear models, including graphical models.  The book contains over 200 problems, many of which may also be used as starting points for undergraduate research projects.  The material can be used by students toward a variety of goals, depending on the degree of theory or application desired.

Keywords

Association and Causation Biostatistics Categorical data analysis Causal analysis Data analysis Exponential family Graphical models Latent class analysis Log-linear models Markov properties Simpson's paradox Social Statistics Survey Analysis

Authors and affiliations

  • Tamás  Rudas
    • 1
  1. 1.Center for Social SciencesHungarian Academy of SciencesBudapestHungary

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-7693-5
  • Copyright Information Springer Science+Business Media, LLC, part of Springer Nature 2018
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4939-7691-1
  • Online ISBN 978-1-4939-7693-5
  • Series Print ISSN 1431-875X
  • Series Online ISSN 2197-4136
  • About this book
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