Bayesian Hierarchical Modelling using WinBUGS/OpenBUGS

Dates: 17-18th February 2011

Duration: 2 days (9.30am to 5.00pm)

Level: 2/3

Location: The Cathie Marsh Centre for Census and Survey Research (CCSR), University of Manchester.

**** Please note that this course is not taken place at Imperial College London ****

*** Training Bursaries are available to assist eligible participants with the costs of attending these courses ***

The ESRC National Centre for Research Methods (NCRM) is offering training bursaries up to £1000 to enable staff in the UK social science community engaged in research, teaching research methods or supervising research to update their skills. Contract researchers working in HEIs are also eligible for the bursaries. Please note that the bursary scheme is open for applications throughout the year i.e. there are no deadlines for applications. For further information about the bursaries and to apply please see http://www.ncrm.ac.uk/about/funding/training/

Tutor

Professor Nicky Best, Imperial College London.

Course Summary

Many quantitative researchers in the social and health sciences will be required to analyse data with a hierarchical or multilevel structure, or with missing or mis-measured values, at some point in their careers. Bayesian methods offer a natural approach to handling these types of problems, through their ability to specify distributions both for model parameters and for missing or imprecisely measured data. This two-day course provides researchers who already have some basic understanding of Bayesian methods with a more in-depth treatment of applied Bayesian methods for modelling data with complex structure. Prior attendance is recommended on introductory course or familiarity with the basic principles of Bayesian inference and the use of Markov chain Monte Carlo methods and/or experience of using WinBUGS/OpenBUGS software.

Further information and Registration

The registration form for the short course can be found at: http://www.ccsr.ac.uk/courses/bayesianhierarchical/

An introductory course on Bayesian analysis may also be of interest.

Course note now can be found here and practical questions here. Data for the practicals can be downloaded here.