Bayesian Inference of Sample Surveys
Date: 10th - 11th April 2006
Venue: Southampton Statistical Sciences Research Institute, University
of Southampton
Bayesian methods in statistics are increasingly popular, spurred by
advances in computational power and tools. Bayesian inference provides
solutions to problems that cannot be solved exactly by standard
frequentist methods. Students learning the Bayesian approach will obtain
new analysis tools and a deeper understanding of competing systems of
statistical inference, including the frequentist approach. The objective
of this course is to describe the application of the Bayesian approach
to survey sampling, where the focus of inference is on finite population
quantities. The instructor has conducted research in Bayesian methods,
and has developed applications to real-world survey problems.
Speakers
Roderick Little is Richard D. Remington Collegiate Professor of
Biostatistics and Research Professor, Survey Research Center at the
University of Michigan. His areas of research expertise primarily focus
on how to handle missing data in variety of statistical analyses, and
inference from sample surveys. He has published numerous articles on
these topics and was also the Coordinating and Applications Editor of
JASA. He is the coauthor with Donald Rubin of an outstanding book
entitled Statistical Analysis with Missing Data. He is the 2005 Wilks
Award recipient from the American Statistical Association.
Contact
Jane Schofield
ESRC National Centre for Research Methods
School of Social Sciences
University of Southampton
Southampton
SO17 1BJ
Tel: 023 8059 4539
Fax: 023 8059 8908
Email: [log in to unmask]
Website: http://www.ncrm.ac.uk
Hosted by the
University of Southampton
--
Jane Schofield
Administrator
ESRC National Centre for Research Methods
Tel: +44 (0)2380 594539
Fax: +44 (0)2380 598908
|