Dani Gamerman, Instituto de Matemática, Universidade Federal do Rio de Janeiro

Structural equation modeling (SEM) is a very useful tool for psychometrists as relations between latent constructs are frequently built, eg the effect of stress level in the student proficiency. This tool is also valuable in many other areas of Science. Important requirements for the SEM framework is to be able to incorporate effects associated with the passage of time in the so-called dynamic SEM and the generalization to handle non-Gaussian measurements. Dynamic generalized SEM is geared towards accommodating these extensions. We show how to: a) set up a model in state-space format; b) to perform inference; c) to make model selection and predictions and; d) to summarize results obtained from the analysis. Inference is performed with a Bayesian perspective, facilitating the use of MCMC methods and other useful modelling tools, including parsimony and identification. An application on the effect of pollution on health is used to illustrate many of these issues in the context of a real data set from northern Italy. Joint work with Luigi Ippoliti and Pasquale Valentini (Pescara).

ABOUT THE SPEAKER

Dr. Gamerman is Professor of Statistics at UFRJ and Director of their Graduate Program in Statistics. He is also visiting faculty at University College London, Duke University (USA), University of Connecticut (USA), Universidad Rey Juan Carlos (Spain), and ITAM (México). In 1987, he received his Ph.D. in Statistics from University of Warwick. Author of Monte Carlo Markov Chain: Stochastic Simulation for Bayesian Inference (with H. F. Lopes) and Statistical Inference: an Integrated Approach (with H. S. Migon and F. Louzada), both in their 2nd edition. Dr. Gamerman has authored more than 60 papers, published in Biometrika, JRSS B, Statistics & Computing, Multivariate Analysis, JBES, Applied Statistics and other (mostly statistical) journals and book chapters, including for the Handbook of IRT (edited by W. v. d. Linden). He is Associate Editor for the International Statistical Review, Environmetrics, Statistical Modelling, Statistical Methods & Applications, the Brazilian Journal of Probability and Statistics, and formerly for JBES. Lastly, Dr. Gamerman has given plenary talks at a number of scientific meetings, including Valencia International Meeting on Bayesian Statistics and ISBA World Meeting and seminars at universities in the USA, Europe, and Australia.