GLIM 82: Proceedings of the International Conference on Generalised Linear Models

1. Front Matter

   Pages i-vi

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2. Introduction

   • J. A. Nelder

   Pages 1-2

3. Prism — An Overview

   • R. J. Baker

   Pages 3-24

4. GLIM4 — The New Facilities

   • M. R. B. Clarke

   Pages 25-35

5. Array Manipulation in Prism

   • M. Green

   Pages 36-42

6. The Graph Module

   • M. Slater

   Pages 43-57

7. AOV: The Prism Module for Analysing Designed Experiments

   • R. W. Payne

   Pages 58-68

8. The APL Alternative

   • P. J. Green

   Pages 69-75

9. Direct Likelihood Inference

   • Murray Aitkin

   Pages 76-86

10. Score Tests in GLIM with Applications

    • Daryl Pregibon

    Pages 87-97

11. Glim Syntax and Simultaneous Tests for Graphical Log Linear Models

    • Joe Whittaker

    Pages 98-108

12. Compound Poisson Regression Models

    • John Hinde

    Pages 109-121

13. Some Aspects of Parametric Link Functions

    • A. Scallan

    Pages 122-127

14. A Model for a Binary Response with Misclassifications

    • Anders Ekholm, Juni Palmgren

    Pages 128-143

15. Loglinear Models with Composite Link Functions in Genetics

    • R. Burn

    Pages 144-154

16. Use of the Complementary Log-Log Function to Describe Dose-Response Relationships in Insecticide Evaluation Field Trials

    • Kathleen Phelps

    Pages 155-163

17. GLIM for Preference

    • C. D. Sinclair

    Pages 164-178

18. A GLM FOR Estimating Probabilities in Retrospective Case-Control Studies

    • M. Slater, R. D. Wiggins

    Pages 179-184

19. Back Matter

    Pages 185-189

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This volume of Lecture Notes in Statistics consists of the published proceedings of the first international conference to be held on the topic of generalised linear models. This conference was held from 13 - 15 September 1982 at the Polytechnic of North London and marked an important stage in the development and expansion of the GLIM system. The range of the new system, tentatively named Prism, is here outlined by Bob Baker. Further sections of the volume are devoted to more detailed descriptions of the new facilities, including information on the two different numerical methods now available. Most of the data analyses in this volume are carried out using the GLIM system but this is, of course, not necessary. There are other ways of analysing generalised linear models and Peter Green here discusses the many attractive features of APL, including its ability to analyse generalised linear models. Later sections of the volume cover other invited and contributed papers on the theory and application of generalised linear models. Included amongst these is a paper by Murray Aitkin, proposing a unified approach to statistical modelling through direct likelihood inference, and a paper by Daryl Pregibon showing how GLIM can be programmed to carry out score tests. A paper by Joe Whittaker extends the recent discussion of the relationship between conditional independence and log-linear models and John Hinde considers the introduction of an independent random variable into a linear model to allow for unexplained variation in Poisson data.

• Random variable
• likelihood
• modeling
• statistics

• Department of Mathematics, The Polytechnic of North London, Holloway, London, England

  Robert Gilchrist

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