I'm working on longitudinal data of quality of life from a clinical research. I would like to use this analysis to assess changes in quality of life scores over the time and identify key predictors in the two groups.
I'm not sure why you need to use non-parametric data, unless you have a single ordinal item for quality of life. If you have multiple items that go into a quality of life scale, then you should look at a thread I started that provides some basic resources on scale construction.
It seems that you should be able to use an appropriate parametric longitudinal model for your analysis. A general estimating equation (GEE) model will allow you to choose the appropriate family and link, given your data type and distribution.