I am choosing summary statistics for percentage data that is clustered near 100%. Each subject takes the same test twice. Each test consists of at least 40 questions. I want to be able to predict which subjects will improve more. I have a hypothesis that subjects with higher variability of performance in the first test will improve more. To test this, I computed the variance of each subject's per-question scores, and indeed those with higher variance improved more. But the problem is that the presence of the threshold introduces an artefact: subjects with near-100% performance to start with can't improve much and also may have lower variance simply because the upper tail of question scores is limited by the maximum score threshold. Inter-quartile range would suffer from the same problem. I will try "one-sided variance" (using only question scores lower than the mean), and "lower quartile to median range". Any other ideas, and does anyone know of a use in the literature of something like this?