I am currently trying to find the best way to analyse my data.
Participants were tested longitudinally on up to five occasions. On each day participants were assessed for the presence or absence of a neurological marker (dichotomous), and were tested on a continuous measure (scoring 0-10). I simply want to compare how the positive or negative diagnosis on any given occasion predicted score on the continuous measure.
Unfortunately as the study took place in a critical-care hospital ward participants were all tested a different number of times, and were positive or negative for varying proportions of these observations. The distributions of scores for each group on the continuous variable were also non-normal.
So, I was wondering if there was a non-parametric repeated measures test that could handle unbalanced designs? I have been told Multi-level modelling might be an option, but I don't have much experience with it.
Thanks in advance for any help!