Workshop: Week 7

Instructions

Pick one of the following tasks and work as a group, guided by the group navigator.
While this week focusses on regression models with categorical predictors and the tasks below are for you to practice them, you should also get summary measures and plot the data, so that you familiarise yourself with the data sets and you keep practising skills learned in earlier weeks.

When completing your chosen task, you are expected to:

Learn about the task data by reading the linked data docs.
Use a Quarto document for your code and text.
Read the data and familiarise yourself with it. As mentioned above, you should calculate summary measures and create plots of relevant variables (based on the given research question).
Work out and discuss the mathematical formula of the regression model to fit to answer the research question.
Fit the regression model.
Discuss the summary, plot and calculate summaries of the posterior draws of the coefficients and expected values.
Write a result paragraph where you report the model specification and the results.

Task A: Vowel duration and vowel category

Task B: Pupil width

Data docs.
Data: mclaughlin2023/pupil-width.csv.
Is the average maximum pupil size (pupil_max) different when recognising words from dense lexical neighbourhoods compared to words from sparse lexical neighbourhoods (Condition)?
Discuss the results with your group (no need to write the discussion).

Task C: Shallow Structure Hypothesis

Data docs.
Data: song2020/shallow.csv.
Filter the data so it contains only L2 data (Group) and critical trials (Critical_Filler).
How does relation type of prime-target (Relation_type) affect reaction times (RT) in L2 speakers of English?
Discuss the results with your group (no need to write the discussion).