I developed a re-coloring algorithm to make maps more accessible to the color vision impaired. In order to test this algorithm, I created a questionnaire in which participants answered questions about maps with confusing colors (red and green) and re-colored maps. This questionnaire format was based on the work of Cynthia Brewer. Map order was random.
There were two groups of participants: 41 subjects with normal color vision (passed D15 panel arrangement test) and 41 subject with a color vision impairment (failed D15 test). Each participant has three variables: questionnaire score using original maps (0 - 100), questionnaire score using re-colored maps (0 - 100) and color vision classification (0,1).
I have read about using gain scores with ANCOVA for this type of data. I thought I could treat the original map scores as a pre-test and the re-colored map scores as a post test. Unfortunately, these scores are not normally distributed. Also, a participant can only improve a finite amount. For example, if the participant scored 90% on the original map questionnaire, they can only improve at most 10% using the re-colored maps. Is it valid to also use the pre-test score as a covariate?
I am using R to run this analysis.