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I have conducted an experiment where several students assigned to two different groups had to solve 13 different puzzles each in two different sessions. Thus, we have 2 sessions, and two different tasks with 13 puzzles each are needed to be solved.

For example: if subjects solve 1 puzzle within a task, they completed 1/13 or 7.6% of the task, if they solved all puzzles, they have completed 100% of the task.

Then my dependent variable goes from 0 to 100% (100% of productivity if all puzzles are solved) in each of the sessions.

The data might look like this: SUBJECT SESSION TASK PRODUCTIVITY 1 1 2 20% 1 2 1 10% 2 1 1 50% ...

I heard that a Linear Mixed Model (LMM) considers that the dependent variable is not restricted between 0 and 100. Do you know how may I analyze those cases with a LMM?

May I use nlme or lmer?

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    $\begingroup$ Did each student get the same set of puzzles? If so, is the raw data (i.e. whether a puzzle was solved or not) available? $\endgroup$
    – matus
    Commented Apr 12, 2017 at 10:51
  • $\begingroup$ Yes to both questions $\endgroup$
    – Adrian Santos
    Commented Apr 12, 2017 at 14:08

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