Course
Dates & Location
This course is structured as a block seminar. At the beginning of the semester, presentation topics will be assigned, and these topics should be worked on in pairs throughout the lecture period. At the end of the lecture period, the groups will present their presentations to the other participants over the course of 4 sessions. The following 4 dates have been allocated for this purpose:
| Date | Time (c.t.) | Place | Topics |
|---|---|---|---|
| Monday, January 22, 2024 | 8:00-12:00 am | Math building E27 | Intro, Random-effects structure |
| Friday, January 26, 2024 | 2:00-6:00 pm | Math building E21 | Shrinkage, Model selection I + II |
| Monday, January 29, 2024 | 8:00-12:00 am | Math building E27 | MGLM I + II, Longitudinal Data |
| Friday, February 2, 2024 | 2:00-6:00 pm | Math building E21 | Big Data, Reporting Results |
Note: Attendance is mandatory for all four sessions.
Course Plan
At the beginning of the semester, we will assign presentation topics and form pairs for presentations. The presentation of the topics will take place at the end of the lecture period.
| # | Date | Content |
|---|---|---|
| 1 | 16.10.2023 | We provide an overview of potential topics. |
| 2 | until 23.10.2023 | Suggestions for own topics/groups can be submitted. |
| 3 | until 30.10.2023 | Participants provide their topic preferences. |
| 4 | 27.10.2023 | Announcement of the final assignment of each participant to a group / topic |
| Independent work on each respective topic. | ||
| 5 | until 31.12.2023 | One individual appointment with the lecturer per group |
| Independent work on each respective topic. | ||
| 6 | 31.01.2024 | Introduction + Presentations |
| 7 | 30.01.2024 | Presentations |
| 8 | 26.01.2024 | Presentations |
| 9 | 02.02.2024 | Presentations + FAQ |
| 10 | until 31.03.2024 | Submission of tutorial via upload in Moodle |
Comments:
- to 2) We would like to offer you the opportunity to shape the seminar content, according to your interests: Thus, if you are interested in a particular scientific paper or a topic related to multilevel modeling (Frequentist or Bayesian), you can propose it. We created in Moodle a respective discussion topic Topic suggestions. We will then discuss the suitability of the topic. If two or more students are already interested in the same topic and wish to form a group, that is possible. Otherwise, participants will be grouped based on their interests.
- to 3-4) We will conduct a survey on Moodle for the preference selection and inform you in advance.
- to 5-8) Attendance is mandatory during the sessions (even if you are not giving a presentation yourself!).