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I want to conduct a within-subjects experiment with one independent variable with four levels. However, I ran a few informal pilot tests, and exposing participants to all four conditions seems to negatively affect results on the later conditions. That is, participants get bored of the experiment by the second or third treatment, and this shows in their responses.

If possible, I would like to expose participants to only two of the treatments (properly cross-balanced) but have no clue how to analyse the data then as, I think, a normal RM ANOVA would expect participants to have values for all four treatments.


NB: This might have been asked before, but the closest question I could find had different underlying assumptions, namely, that different "treatments" (in this case, different questions on a questionnaire) do not have any influence on each other).

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In your case you'd need to perform a multi-level model. But, given that you already conceded that you believe the treatments are influencing each other you really should just design your study between. Unless you desire to specifically analyze how treatments influence each other use a between S design.

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  • $\begingroup$ Sorry for not coming back to this sooner. I am indeed interested in how the treatments influence each other. I've been looking into crossover designs and multi-level models to some extent but most repeated-measures examples I've found seem to involve measuring the effect of one treatment over time rather than of multiple treatments on the same subject, and I am not sure how to develop a model that involves treatment (A, B, C, D), order (1st, 2nd, 3rd, 4th) and sequence (e.g. A-1st, C-2nd, B-3rd, D-4th) $\endgroup$
    – ThomasH
    Nov 26, 2012 at 0:04
  • $\begingroup$ they're just additional factors in the model $\endgroup$
    – John
    Nov 26, 2012 at 2:23

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