In the package mecor, regression calibration methods and a maximum likelihood method are implemented to correct for measurement error in a continuous covariate in regression analyses.
When predictors in such models are highly collinear, unexpected or spurious predictor-outcome associations may occur, thereby potentially reducing face-validity and explainability of the prediction model.
Dimensionality Reduction Methodology 60 G.3
Data mining and machine learning techniques such as classification and regression trees (CART) represent a promising alternative to conventional logistic regression for propensity score estimation.
Although such heterogeneity in predictor measurement across derivation and validation samples is very common, the impact on the performance of prediction models at external validation is not well-studied.