Applying Generalized Linear Models

  • James K. Lindsey

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

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Pages 27-47
  3. Pages 69-86
  4. Pages 87-107
  5. Pages 109-119
  6. Pages 121-140
  7. Pages 141-158
  8. Pages 159-171
  9. Pages 173-196
  10. Back Matter
    Pages 197-257

About this book

Introduction

Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liège, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books.

Keywords

ANOVA Analysis of variance Excel Fitting Generalized linear model Measure Probability distribution Time series best fit linear regression

Authors and affiliations

  • James K. Lindsey
    • 1
  1. 1.Department of BiostatisticsLimburgs Universitair CentrumDiepenbeekBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/b98856
  • Copyright Information Springer-Verlag New York, Inc. 1997
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98218-2
  • Online ISBN 978-0-387-22730-6
  • Series Print ISSN 1431-875X
  • About this book