MIXED MODELS ANALYSIS OF MEDICAL DATA USING SAS
Edinburgh, 9-11 October 2013
Course content:
This course will cover the statistical background to the mixed model and will emphasise its practical application in medical data with particular reference to clinical trials. All analyses will be illustrated using SAS and lectures will be combined with practical sessions in order to reinforce concepts.
Topics covered include:
Day 1
- General concepts and underlying statistical theory
- Use and interpretation of PROC MIXED
- Multi-centre trials and meta-analysis
- Consideration of issues such as biased standard errors, significance testing and negative variance components
Day 2
- Repeated measures trials
- Random coefficients models
- Crossover trials
- More complex trial designs
- Introduction to simulation methods, in particular MCMC
Day 3
- Generalised linear mixed models
- Mixed models for ordinal data
- Fitting GLMMs with PROC GLIMMIX, PROC GENMOD and PROC MCMC
Note the practical sessions will focus on constructing models and interpreting results from PROC MIXED output, and are not "hands-on".
Who should attend:
This course is directed at medical statisticians who wish to understand the statistical background to mixed models and to carry out analyses using SAS.
Why attend:
Conventionally, clinical data is analysed using fixed effects models. However, benefits can often be gained by using a mixed model. For example: in repeated measures trials full allowance can be made for the correlation occurring between the repeated observations even if data are missing; in multicentre trials or meta analyses treatment standard errors are more appropriately based on between centre/trial variation (fixed effects standard errors are based on within centre/trial variation); in crossover trials more accurate treatment means are often achieved by combining within and between patient estimates. Suitable procedures are now readily available for fitting these models well known packages such as SAS. This has led widespread application and knowledge of mixed models becoming essential for medical statisticians.
As with any statistical technique a firm understanding of the theoretical background is essential to allow its effective application and to obtain a clear interpretation of results.
Course fees:
Standard rate £850
Registered charities/academic institutions £650
Fees include lunches, a course dinner and a delegate's pack including full course notes.
The speakers:
Dr Helen Brown is the Senior Statistician at The Roslin Institute, University of Edinburgh. She has over twenty five years of practical experience as a statistician and has been employed within academia, the health service and the pharmaceutical industry. She has a research interest in the use of mixed models in medicine and is co-author of Applied Mixed Models in Medicine, in the John Wiley Statistics in Practice series.
Robin Prescott is Emeritus Professor of Health Technology Assessment at the University of Edinburgh. Previously he was Director of the Medical Statistics Unit at the University. He has been working in the medical field for over thirty years and has a particular interest in cross-over trials. He has wide experience of multi-centre trials and of working with the pharmaceutical industry.
Venue:
The course will take place at Paterson's Land, University of Edinburgh , Holyrood Road, Edinburgh, EH8 8AQ, conveniently located in the city centre. Accommodation is available within 5 minutes walking distance, discounts will be offered to delegates at selected hotels.
Further information:
Course website: http://www.lifelong.ed.ac.uk/mixedmodels/
Course administrator: [log in to unmask] or telephone +44 (131) 651 1889/1180.
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The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
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