My data look like this: The dependent variable is score on a language task (numerical). I have $2$ between subject variables:
- age (young vs old: categorical)
- language (monolingual vs. bilingual: categorical)
Then, I have $3$ within-subject variables (task conditions):
- verb type (2 values: categorical)
- focus (2 values: categorical)
- definiteness (2 values: categorical)
There are two random effects:
I run an
lmer model in R. I want to include random intercepts and random slopes.
Question: Does it make sense to include random slopes for within-subject (so
definiteness) factors for RE subject and random slopes for between-subject factor (so
language) for RE item?
If yes, the model would look like this, so all factors as random slopes for both random effects:
lmer(score ~ age * language * verbtype * focus * definiteness + (1+age+language+verbtype+focus+definiteness|subject) + (1+age+language+verbtype+focus+definiteness|item), data)
Intuitively, I feel like it does not make sense to include between-subject factors (
language) as random slopes for subject and between-item factors (
definiteness) as random slopes for item.
If this intuition is correct, the model would be:
lmer(score ~ age * language * verbtype * focus * definiteness + (1+verbtype+focus+definiteness|subject) + (1+age+language|item), data)
Which one of these models makes more sense?