This spring I will run a motor learning experiments
with elite alpine ski racers. I plan to run a between-subjects experimental design with pre and post data. I am going to have pseudoreplication on pre and post, because each participant perform five trials. What is an appropriate statistical model for this data?
Here are my initial thoughts:
I can aggregate the performance on pre and post, and run a simple ANCOVA. In this case my model will look something like this:
My model will look something like this:
post_i ~ constant + pre + group + error_i.
But that approach will through away information. Is it possible to run a multilevel “ANCOVA” variant on these data, such that I can use all trials in the model without calculating an average score for each participant?
If not, I think I can run a multilevel growth model. With lme4 formula it will be something like this:
performance_i ~ 1 + time + group + time:group (1 + time | participant)
This will help me include all trials in the model but will have slightly lower power compared with the ANCOVA model (my intuition). But if there is a way to run an ANCOVA with pseudoreplication, that would be very useful.