3 papers
Comparing Imputation Methods for Clinical Prediction Model Development under Complex Missingness Scenarios: A Simulation Study Using Real-World Cardiac Data
Pakpoom Wongyikul, Noraworn Jirattikanwong, Natthanaphop Isaradech +4
Evidence remains limited on how missing-data strategies affect the stability of clinical prediction models across different predictor-outcome relationships and degrees of missingne…
Class Imbalance Corrections Failed to Enhance Discrimination, Model Calibration, and Prediction Stability: An Empirical Simulation Study Based on Clinical Dataset
Wachiranun Sirikul, Natthanaphop Isaradech, Wuttipat Kiratipaisarl +3
Class imbalance is common when developing clinical prediction models (CPMs) and is often assumed to lead to poor predictive performance. Several methods have been proposed to corre…
Influence of continuous predictor modelling methods on prediction stability in clinical prediction model development: an empirical comparison using real clinical data
Phichayut Phinyo, Pakpoom Wongyikul, Noraworn Jirattikanwong +5
Background and objective: Prediction stability is increasingly recognised as important for reliable clinical prediction model development, but the effect of continuous predictor mo…