Mixed models with medical and engineering applications

A useful reference regarding practical aspects of fitting mixed models in R is Faraway, J.J. (2006) Extending the linear model with R, Chapman and Hall/CRC, chapter 2 and 8.

Details on fitting linear mixed models in SPSS are provided in these notes.

Some data sets and R-code used in the course. The orthodontic data set "Orthodont" is a part of the nlme R package.

Participants are evaluated as passed/failed based on attendance and assessment of hand-ins.

Location October 11: Fredrik Bajers Vej 7C room 2-209. Location October 14: online (Teams).

DEADLINE for hand-ins is 12:00 Monday October 25.

1 Monday October 11 8.15-12.00: Slides (with exercises). Primer (updated 04.10.21) on covariance. Exercises to be handed in: 1, 2 and 3. Also think carefully about the questions in exercise 4. We'll have a plenary discussion of exercise 4 on Thursday.

2 Monday October 11 12.30-16:00: Slides (with exercises) and spss-screen shots. Hand-in: exercise 2 and 3.

3 Thursday October 14 8.15-12.00: Recap slides (updated 12.10.21, see link above for code). Mixed models with correlated noise. Logistic regression (updated 12.10.21) with random effects (updated 12.10.21).

4 Thursday October 14 12.30-16.00: (attendance not mandatory) you work on exercises and possibly mixed model analysis of your own data. I will be around to help.

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