I just started reading about multilevel modeling so I can apply the method to my research data. However, I have yet to come across an illustrative example or even discussion how to organize and set up a model for a repeated-measures design with a grouping variable to counterbalance across materials.
For example, let’s say I want to look at the effect difficulty level of paragraph has on time to read a target sentence embedded within each paragraph. To test this, I create 6 paragraphs, in which there are three versions of each paragraph: Difficult (D), Moderate (M), Easy (E). Participants get exposed to all three levels of difficulty but only read one version of each paragraph. So, reading material is repeated-measures, but the specific paragraph participants get differs. To counterbalance across difficulty levels, participants also get different orders of conditions with the restriction that each condition appears in each position an equal number of times (this is the grouping variable; order is a between subjects variable)
So, for the sake of counterbalancing, I administer three different orders of the six paragraphs for the following participants: Beth: DME EDM (order 1) John: MED DME (order 2) Mary: EDM MED (order 3)
So, you can see that everyone gets all levels of difficulties but for different paragraphs.
The dependent measure is the time to read a target sentence for each paragraph. Here is a tabular display of fictitious data of reading time laid out by the experimental design:
So, my first question is, how do I organize the data to prepare for MLM to reflect the order grouping variable and three levels of difficulty, repeated measures? Then how should I start thinking about incorporating random effects into the model?