Gaur-gaurkoak

The course is intended to review the basic theory of linear mixed models from a classical point of view and from a Bayesian perspective. The course will then focus on model diagnosis and a well known spatial mixed effects model for count data, the so called Besag-York-Mollié (BYM) model.

REGISTRATION REQUIRED:  Click on this link.

REGISTRATION DEADLINE: 3rd October

INSTRUCTOR:

James Hodges is Professor at the Division of Biostatistics and Health Data Science, University of Minnesota. His statistical research is in the area of hierarchical and other richly parameterized models. Professor Hodges works with University researchers in a variety of health related fields. Over the years, his areas of particular emphasis have included pediatric, and kidney disease endocrinology, oral-health research, infectious diseases, and neurology. He has also collaborated with researchers at the Minneapolis VA Medical Center’s Center for Chronic Disease Outcomes Research. Outside of health-care research, he has collaborated with researchers in demographics, wildlife management, ornithology, horticulture, combat analysis, military logistics, simulation models, airport safety, and marketing. He is Fellow of the American Statistical Association, and he has received several awards: Excellence Advising Award (School of Public Health, University of Minnesota, 2016), Clinical Research Award (American Academy of Periodontology, 2007), and Dick Wittink Award  for the best paper in Quantitative Marketing and Economics (2019), among others. Professor Hodges has an outstanding academic career and he has published articles in the most recognized statistical journals (Journal of the American Statistical Association, The American Statistician, Biometrics, Journal of the Royal Statistical Society, Series B…)