Presented by Helen Brown (University of Edinburgh) and Eleanor Allan (Honorary Fellow, University of Reading)
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. The course will be based on material from the textbook Applied Mixed Models in Medicine by Helen Brown and Robin Prescott, and delegates will each receive a copy of the latest edition.
The course is directed at medical statisticians who wish to understand the statistical background to mixed models to carry out analyses using SAS.
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.