I am trying to learn how to analyze data using linear mixed effects. Specifically, I'm not sure how to handle a grouping variable that's part of my data set.

Here's a sample scenario: Let's say I am interested in the effect difficulty has on the time to read short paragraphs. There are three versions of each paragraph: Easy, Moderate and Hard and difficulty is repeated-measures. So, each subject will read 6 short paragraphs, 2 at each level of difficulty.

I will also construct a grouping variable to control for order of condition. Subjects will be assigned to one group (so essentially, I have an independent groups variable). In this case, each group will contain a specific sequence of the paragraphs in the conditions. For example, Group 1 will get Paragraphs 1 & 5 in the easy condition, paragraphs 2 & 6 in the moderate condition and 3 & 4 in the difficult condition. Group 2 will get paragraphs 3 & 4 in the easy condition, 1 & 5 in the moderate condition and 2 & 6 in the difficult condition. Group 3 will receive Paragraphs 2 & 6 in the easy condition, Paragraphs 3 & 4 in the moderate condition and paragraphs 1 & 5 in the difficult condition.

So, when I lay out the data in long format, I have something like:


My fixed effect is difficulty and random effects are subject and items. However, I'm not sure how to treat the grouping variable. Can I just eliminate the grouping variable -- when items are included, the grouping variable seems redundant. If I can't eliminate the grouping variable, should I treat it as a fixed effect or random effect? The grouping variable is not of interest -- it's just a sequence of items that move together across conditions.

I apologize if I have not been clear -- as I indicated I am learning LMM now. But thank you for your help and advice you can give.


1 Answer 1


From what I understand of the study design, the grouping variable is simply based on the paragraphs read. Therefore, if you include paragraph as a grouping variable for random intercepts, for example using:

time ~ difficulty + (1 | paragraph) + (1 | subject)

then you will not need to include group in the model at all.


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