I've recently asked whether it is valid to treat repeated measures data as both within- and between-subject data and compare the analysis of both to see if there are differences. My question was motivated by a particular paper (PDF) about presence questionnaires that, in my opinion, implied that such questionnaires are essentially not applicable in between-subject designs, as people would only be able to reliably rate their sense of presence in a particular environment relative to another environment.
This assumption was questioned by some of the answers, and hence I was wondering whether treating the same data as between-subjects and within-subjects data can ever lead to a systematic difference. That is, is it possible that an effect will show up if I analyse data as within-subjects but not show up when analysed as between-subjects?
By way of a very contrived example, assume I get subjects to rate on a scale of 1 to 10 how much they like an offer of free beer. In one condition, people are offered one litre of beer for free, in the second condition, people are offered two litres of beer for free. If I ran this experiment with a between-subjects design, I would personally assume that there isn't any discernible difference between the two conditions, because - hey, free beer! But as a within-subjects design, I think I stand a reasonable chance of seeing an effect, because more free beer is better than less free beer.