Model calibration
From calibration standpoint, the main effect model and machine learning
algorithm (fig S1a and S1b) were well calibrated in the lower segment of
predicted probability (0-5%). Beyond this probability range, the main
effect model did not seem well calibrated due to perhaps the absence of
adequate number of parameters (in other words, misspecification error in
the 5% to 100% probability range) resulting in risk over-estimation.
The ML based algorithm overestimated the risk beyond 5% (beyond the
range of operation), but had better calibration than that obtained for
the main effect model.