I have a Songbird model that looks like it almost outperforms the null model as shown here:
This are my parameters:
--formula "C(Score_3, Treatment('low'))+bmi"
My cohort is of 432 and I did a Train-test split of 60:40.
This is the best I've been able to get after playing around with the parameters for a couple of days now. As seen on the graphs, the null briefly overlaps the model but then dips lower, and the Q2 value is negative. There is a significant difference in beta diversity between the groups of interest (weighted unifraq, p = 0.04), so from my understanding, I should be able to get some meaningful results from Songbird.
Does this look ok to move on with downstream analysis? Do you have any suggestions on how to improve the model?