DARIO GREGORI, GILBERT MACKENZIE, HERWIG FRIEDL, ROBERTO CORRADETTI (edited by)
Correlated Data Modelings 2004
Scientific Meeting in Honour of Diego de Castro
Franco Angeli, Milano, 2007, pp. 400

Models for correlated data are appearing as one of the most vital and exciting fields of the statistical methodology. Random effects models and estimative equations are only two of the major schemes used for dealing with the impressive mass of potential relevant applications. These are ranging from spatial analysis up to designs using repeated measures on the same subjects, with applications in classical bio-medical fields as in public health and economics, up to political sciences and sociology.
In the second edition of the workshop (the first was organized in Trieste in 1999), organized in Turin in January 2004, we proposed to investigate the relationships among the various approaches and models as proposed in the various fields of application, and in particular in biometrics and econometric modelling.
The final goal of this edition of the workshop was to improve contacts between application and methodology, as developed in the applied contexts where the models have been proposed.
According to the contributions included in this volume, we can affirm that the workshop was quite success. We have important contributions from various field of application, like econometrics, education and behavioral sciences, law, biomedicine, jointly to excellent papers on more methodological aspects.
All the Editors feed obliged to thank all authors for having contributed to this workshop and to this volume. A special thanks for Alessandra Durio, Ennio Isaia, Eugenio Novelli, Aldo Goia, Rosalba Rosato for the great help in organizing the workshop. A particular appreciation is deserved to Silvia Snidero, who cared fotr the collection and the editing of the papers.

The Editors

Contents
Covariance & Dispersion Modelling

• J.A. Nelder, Extended Likelihood Inference applied to a New Class of Models
• J. Pan, G. MacKenzie, Joint Modelling of Mean and Covariance Structures in Logitudinal Studies
• G. MacKenzie, J.X. Pan, Optimal Joint Mean-Covariance Modelling
• C.T. Jose, B. Ismail, Estimation of Error Correlation in Nonparametric Regression
• M. Pourahmadi, Simultaneous Modelling of Covariance Matrices: GLM, Beyesian and Nonparametric Perspectives

• Wedlin, About multidimensional statistical models
• S. Centanni, M. Minozzo, Estimation and Filtering by Reversible Jump MCMC for a Doubly Stochastic Poisson Model for Ultra-High-Frequency Financial Data
• C. Genovese, R. Renò, Modeling international market correlations with high frequency data
• R.C. Jung, A.R. Tremayne, Estimation and testing in time series models with integer support
• R. Bernardini Papalia, Combining Incomplete Information and Learning in Microeconometric Models: a Generalized Cross Entropy Approach

• V. Di Giacinto, Forecasting multivariate spatial time series with a common factor model
• D. Catelan, E. Dreassi, A. Biggeri, C. Lagazio, Space-time models with time dependent covariates
• S. Toti, A. Biggeri, A. Baldasseroni, A hierarchical Bayesian model for a variability analysis of measurements of occupational n-hexane exposure in Italy
• E. Novelli, Statistical Modelling of Epidemiological Data on Cancer Diseases
• M.M. Maule, G. Migliaretti, D. Mirabelli, S. Bellini, A. Castella, A. Chiò, F. Merletti, F. Cavallo, Bayesian methods in the analysis of mortality associated to central nervous system diseases in Piedmont, Italy (1992-1997)

• O. Paccagnella, Duration Data and the Discrete - Time Multilevel Hazard Model: An Application to Compare Vocational Training Courses
• M. Blagojevic, G. MacKenzie, A Comparison of PH and Non-PH Frailty Models
• P. Del Bianco, R. Borgoni, A multilevel Heckman-type model for longitudinal quality of life data subject to drop out in a multi-centre clinical trial
• F. Siannis, Sensitivity Analysis for Informative Censoring; A Semi-parametric Approach

• G. Dahmen, I.R. König, A. Ziegler, Investigation of familial aggregation by generalized estimating equations: Application of alternating logistic regression and Prentice's method
• L. Grilli, C. Rampichini, A multivariate multilevel model for the analysis of graduates' skills
• N.H. Spencer, A. Fielding, Estimation and comparison of endogenous ordered category multilevel models
• D. Coin, Unmasking multivariate outliers and multiple models in an econometric application
• D. Ferrante, P. Donato, P. Soldà, C. Magnani, F. Della Corte, Statistical analyses of outcome predictors after severe traumatic brain injury
• R. Rosato, D. Gregori, A. Biggeri, A competing risk model to estimate the hospitalizations of a cohort of diabetic patients. The additive regressioon model
• A. Ferrando, D. Gregori, A. Russo, R. Arione, M.C. Azzolina, M. Piobicci, G. Ciccione, Factors affecting hererogeneity among hospitals in preventing pressure ulcers: a GEE investigation on the EPUAP study