During the first couple of weeks multipple linear
regression will be revied, and some important points
emphasized. Then models also containing
random effects will be discussed. The last part of the
course will be om longitudinal models, covering the
syllabus in Fitzmaurice et. al.
- Week 3 (1/17-1/21): Summary of inference in linear models:/studier/emner/matnat/math/STK4070/v11/undervisningsmateriale/not01_11.pdf
- Week 4 (1/24-1/28): Continuation of summary of linear models, especially analysis of variance, a summary here: /studier/emner/matnat/math/STK4070/v11/undervisningsmateriale/not03_11.pdf.
- Week 5 (1/31-2/4): Start of components of variance, a summary here: /studier/emner/matnat/math/STK4070/v11/undervisningsmateriale/not04_11.pdf
- Week 6 (2/7-2/11): More components of variance.
- Week 7 (2/14-2/18): Matrix formulation for models with random effects. Longitudinal studies: Basic problems, notation and distributional assumptions, chapter 1-3 (except 3.6) in FLW.
- Week 8 (2/21-2/25): Finish chapter 3 (except 3.6) in FLW. Then chapter 4 on estimation and statistical inference.
- Week 9 (2/28-3/4): Finished chapter 4 statistical inference, REML and missing observations.
- Week 10 (3/7-3/11): Chapter 5 on modelling the mean: analyzing response profiles, sections 5.6 and 5.7 will be skipped initially. Some relevant R-code is here: /studier/emner/matnat/math/STK4070/v11/undervisningsmateriale/tlc_c.R
- Week 11 (3/14-3/18): Chapter 6 on modelling the mean: Parametric curves,
- Week 12 (3/21-3/25): Chapter 7: Modelling the covariance.
- Week 13 (3/28-4/1): Rest of chapter 7. First part of chapter 8: Linear mixed effects models, 8.1-4.
- Week 14 (4/4-4/8): Rest of chapter 8:8.5-8 and 8.10, and chapter 9: Residual analysis.
- Week 15 (4/11-4/15): Chapter 9: Residual analysis and Chapter 10: Review of GLMs.
- Week 17 (4/26-4/29): Rest of Chapter 10, section 10.3 illustrative examples and chapter 11.1-2.
- Week 18 (5/2-5/6) and last lecture: Chapter 11: sections 11.3 and 11.6 and chapter 12.1-4.