The Analysis of Categorical Data Using GLIM

  • James K. Lindsey

Part of the Lecture Notes in Statistics book series (LNS, volume 56)

Table of contents

  1. Front Matter
    Pages I-V
  2. James K. Lindsey
    Pages 1-24
  3. James K. Lindsey
    Pages 25-50
  4. James K. Lindsey
    Pages 51-62
  5. James K. Lindsey
    Pages 63-77
  6. James K. Lindsey
    Pages 78-96
  7. James K. Lindsey
    Pages 97-110
  8. Back Matter
    Pages 111-168

About this book

Introduction

The present text is the result of teaching a third year statistical course to undergraduate social science students. Besides their previous statistics courses, these students have had an introductory course in computer programming (FORTRAN, Pascal, or C) and courses in calculus and linear algebra, so that they may not be typical students of sociology. This course on the analysis of contingency tables has been given with all students in front of computer terminals, and, more recently, micro­ computers, working interactively with GLIM. Given the importance of the analysis of categorical data using log linear models within the overall body of models known as general linear models (GLMs) treated by GLIM, this book should be of interest to anyone, in any field, concerned with such applications. It should be suitable as a manual for applied statistics courses covering this subject. I assume that the reader has already a reasonably strong foundation in statistics, and specifically in dealing with the log-linearllogistic models. I also assume that he or of GLIM itself. In she has access to the GLIM manual and to an operational version other words, this book does not pretend to present either a complete introduction to the use of GLIM or an exposition of the statistical properties of log-linearllogistic models. For the former, I would recommend Healy (1988) and Aitkin et al (1989). Por the latter, many books already exist, of which I would especially recommend that of Pingleton (1984) in the present context.

Keywords

Markov chain Odds biology economics population statistics

Authors and affiliations

  • James K. Lindsey
    • 1
  1. 1.Faculté d’Economie, de Gestion et de Sciences SocialesUniversité de LiègeLiègeBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4684-7448-0
  • Copyright Information Springer-Verlag New York 1989
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-97029-5
  • Online ISBN 978-1-4684-7448-0
  • Series Print ISSN 0930-0325
  • About this book