PCA-based extreme sampling on the first principal component of multiple error-prone exposures yields simultaneous efficiency improvements across models in two-phase validation, demonstrated via simulations and NHANES application.
Using the outcome for imputation of missing predictor values was preferred.Journal of Clinical Epidemiology.2006;59(10):1092–1101
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Two-phase validation sampling via principal components to improve efficiency in multi-model estimation from error-prone biomedical databases
PCA-based extreme sampling on the first principal component of multiple error-prone exposures yields simultaneous efficiency improvements across models in two-phase validation, demonstrated via simulations and NHANES application.