Programme
This is the preliminary program. Individual time slots are subject to minor changes.
Location: CITEC, room 1.024 on 1st floor
DAY 1: Wednesday, Sept 9, 2026
| Time | Session |
| 09:00–10:00 | Invited Speaker |
| 10:00–10:20 | Coffee Break |
| 10:20–10:40 | Talk 1 |
| 10:40–11:00 | Talk 2 |
| 11:00–11:20 | Talk 3 |
| 11:20–11:40 | Talk 4 |
| 11:40–12:00 | Talk 5 |
| 12:00–12:20 | Talk 6 |
| 12:20–13:00 | Lunch |
| 13:00–13:20 | Talk 7 |
| 13:20–13:40 | Talk 8 |
| 13:40–14:00 | Talk 9 |
| 14:00–14:20 | Talk 10 |
| 14:20–14:40 | Talk 11 |
| 14:40–15:00 | Coffee Break |
| 15:00–15:20 | Talk 12 |
| 15:20–15:40 | Talk 13 |
| 15:40–16:00 | Talk 14 |
| 16:00–16:20 | Talk 15 |
| 16:20–16:40 | Talk 16 |
|
DAY 2: Thursday, Sept 10, 2026
| Time | Session |
| 09:00–10:00 | Invited Speaker |
| 10:00–10:20 | Coffee Break |
| 10:20–10:40 | Talk 17 |
| 10:40–11:00 | Talk 18 |
| 11:00–11:20 | Talk 19 |
| 11:20–11:40 | Talk 20 |
| 11:40–12:00 | Talk 21 |
| 12:00–13:00 | Lunch |
| 13:00–13:20 | Talk 22 |
| 13:20–13:40 | Talk 23 |
| 13:40–14:00 | Talk 24 |
| 14:00–14:20 | Talk 25 |
| 14:20–14:40 | Talk 26 |
| 14:40–15:00 | Coffee Break |
| 15:00–15:20 | Talk 27 |
| 15:20–15:40 | Talk 28 |
| 15:40–16:00 | Talk 29 |
| 16:00–16:20 | Talk 30 |
| 16:20–16:40 | Talk 31 |
DAY 3 Satelite Event: Friday, Sept 11, 2026
| Time | Session |
| 09:00–12:00 | Tutorial |
| 12:00–13:00 | Lunch |
Tutorial: Evaluating acceptability through statistical analysis
This tutorial will combine theoretical and hands-on components pertaining to the why and how of analyzing acceptability ratings using two statistical models: Linear Mixed Effects Regression (LMER) and Cumulative Link Mixed Models (CLMM).
First, I will discuss the assumptions for each method and the required data structures. This will be followed by a hands-on session where participants would analyze the data and compare the output of both models.
Participants can bring their own data for the second component.
Alternatively, I will provide a data set for those who have not yet collected their own data.