The project is based on following patients longitudinally at different age categories, with high variability in time of follow-up as well as missing follow-ups.
The data that we are analyzing is parametric and continuous.
We are thinking of plotting a mixed effect model, but is there a robust test to calculate a difference among the samples?
Thanks in advance for any suggestions!
I am not an expert (and I am not quite sure whether I correctly understand your question) but a random effects model should enable you to to estimate effects that do not change within subjects, i.e. the split into 2 or more samples additional to estimating the effects that do change within subjects.
The question is not clear. Mixed effects model is applicable and robust enough. Consider follow-up time as continuous not categorical.
- Badges
- Science topic
- Similar topics
- Mathematical Sciences
- Statistics
- Statistical Software
- SPSS