Markus Brauer and John Curtin have offered this course on general and multi-level linear models. Dr Curtin makes available the syllabi and the power-points for each of his lectures, below. Contact Dr Brauer here for his lectures, if interested.
Syllabi:
Psy 610 – Statistical Analysis of Psychological Experiments
Psy 710 – Design and Analysis of Psychological Experiments
Lecture Materials:
1. Introduction
3. Sampling distributions, parameters and parameter estimates
4. Inferences about a single quantitative predictor
6. Inferences with 2 predictors
9. Dealing with messy data I: Case analysis
10. Model assumptions
11. Power transformation
15. Inferences about two quantitative predictors and their interaction
16. Inferences about two dichotomous predictors and their interaction
19. Polynomial regression
22. Repeated measures designs: Review, design considerations, and an alternative approach
23. Power analysis and statistical validity
26. Model assumptions & case analysis II: More complex designs
27. Missing data: Why you should care about it and what to do about it
30. Planned and unplanned multiple comparisons
31. Graphing – a unified perspective for visual display of data
32. The generalized linear model