Aggregating and Calibrating Prediction Models

Throughout this study, all CPMs will be assumed to be logistic regression models, although the techniques apply to other types of prediction model, such as those for time-to-event outcomes. Stacked regression (SR) [9 (link), 17 ], principal component analysis (PCA) [19 (link), 20 (link)] and partial least squares (PLS) are three possible methods that simultaneously aggregate and calibrate existing models to a new population. We describe SR and PCA here, with PLS described in Additional file 1. This study compares the three aforementioned aggregate approaches with deriving a new model; possible techniques of redevelopment are also outlined in this section.