Introduction to Analysing Repeated Measures Data
Training session with Dr Helen Brown, Senior Statistician, at The Roslin Institute, March 2016.
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These training sessions were given to staff and research students at the Roslin Institute. The material is also used for the Animal Biosciences MSc course taught at the Institute.
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*Recommended YouTube playback settings for the best viewing experience:  1080p HD
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Content:
Mixed model analysis
- Cope with missing data (provided missing at random)
- Treatments effects have suitable SE based on between patient variation
- Treatment effects at individual time points use information from all time points
- Take account of the covariances between of the repeated measurements

Types of mixed model for repeated measures data
- Random effects model
--- Fit patients as random 
- Covariance pattern model 
--- Fit pattern of correlations for observations on the same patient  
- Random coefficients/slopes model 
--- Regression slopes vary randomly between patients