Statistical Modelling

1. Front Matter

   Pages i-ix

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2. NPML estimation of the mixing distribution in general statistical models with unobserved random effects

   • Murray Aitkin

   Pages 1-9

3. Some Topics in Optimum Experimental Design for Generalized Linear Models

   • Anthony C. Atkinson

   Pages 11-18

4. Autoregressive Modelling of Markov Chains

   • André Berchtold

   Pages 19-26

5. A Case—Study on Accuracy of Cytological Diagnosis

   • A. Biggeri, M. Bini

   Pages 27-34

6. Dynamics and Correlated Responses in Longitudinal Count Data Models

   • R. Blundell, R. Griffith, F. Windmeijer

   Pages 35-42

7. Bootstrap Methods for Generalized Linear Mixed Models With Applications to Small Area Estimation

   • James Booth

   Pages 43-51

8. Confidence Intervals for Threshold Parameters

   • R. C. H. Cheng, W. B. Liu

   Pages 53-60

9. Optimal Design for Models Incorporating the Richards Function

   • G. P. Y. Clarke, L. M. Haines

   Pages 61-66

10. Mixed Markov Renewal Models of Social Processes

    • R. B. Davies, G. R. Oskrochi

    Pages 67-74

11. Statistical Inference Based on a General Model of Unobserved Heterogeneity

    • Ekkehart Dietz, Dankmar Böhning

    Pages 75-82

12. An Extended Model for Paired Comparisons

    • Regina Dittrich, Reinhold Hatzinger, Walter Katzenbeisser

    Pages 83-90

13. Indirect Observations, Composite Link Models and Penalized Likelihood

    • Paul H. C. Eilers

    Pages 91-98

14. Model Estimation in Nonlinear Regression

    • Joachim Engel, Alois Kneip

    Pages 99-107

15. Pearson statistics, goodness of fit, and overdispersion in generalised linear models

    • C. P. Farrington

    Pages 109-116

16. M-estimation: Some Remedies

    • Robert Gilchrist, George Portides

    Pages 117-124

17. Subject-Specific and Population-Averaged Questions for Log-Linear Regression Data

    • Ulrike Grömping

    Pages 125-132

18. Radon and Lung Cancer Mortality: An Example of a Bayesian Ecological Analysis

    • Ulrich Helfenstein, Christoph E. Minder

    Pages 133-140

19. IRREML, a tool for fitting a versatile class of mixed models for ordinal data

    • A. Keen, B. Engel

    Pages 141-150

20. Towards a General Robust Estimation Approach for Generalised Regression Models

    • Jayalakshmi Krishnakumar

    Pages 151-160

This volume presents the published proceedings of the lOth International Workshop on Statistical Modelling, to be held in Innsbruck, Austria from 10 to 14 July, 1995. This workshop marks an important anniversary. The inaugural workshop in this series also took place in Innsbruck in 1986, and brought together a small but enthusiastic group of thirty European statisticians interested in statistical modelling. The workshop arose out of two G LIM conferences in the U. K. in London (1982) and Lancaster (1985), and from a num­ ber of short courses organised by Murray Aitkin and held at Lancaster in the early 1980s, which attracted many European statisticians interested in Generalised Linear Modelling. The inaugural workshop in Innsbruck con­ centrated on GLMs and was characterised by a number of features - a friendly and supportive academic atmosphere, tutorial sessions and invited speakers presenting new developments in statistical modelling, and a very well organised social programme. The academic programme allowed plenty of time for presentation and for discussion, and made available copies of all papers beforehand. Over the intervening years, the workshop has grown substantially, and now regularly attracts over 150 participants. The scope of the workshop is now much broader, reflecting the growth in the subject of statistical modelling over ten years. The elements ofthe first workshop, however, are still present, and participants always find the meetings relevant and stimulating.

• Branching process
• Fitting
• Generalized linear model
• Likelihood
• Markov chain
• Time series
• correlation
• linear regression
• mixing
• statistics

• Institut für Statistik, Universität Innsbruck, Innsbruck, Austria

  Gilg U. H. Seeber, Gabriele Steckel-Berger

• Centre for Applied Statistics, Lancaster University Fylde College, Lancaster, England

  Brian J. Francis

• Institut für Statistik, Wirtschaftsuniversität, Wien, Austria

  Reinhold Hatzinger

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