E2P Simulator (Effect-to-Prediction Simulator) is an interactive web-based tool for performing predictive utility analysis - helping researchers understand how their findings will translate into real-world prediction and what effect sizes or model performance is needed to achieve desired levels of predictive and clinical utility. The simulator addresses critical gaps in research practice by placing measurement reliability and outcome base rates at the center of study planning and interpretation.
The tool supports both binary and continuous outcomes, providing analytical solutions and data simulations to explore relationships between effect sizes (Cohen’s d, Pearson’s r, Odds Ratios), predictive performance metrics (ROC-AUC, Sensitivity, Specificity), and real-world predictive value and clinical utility measures (PPV, NPV, PR-AUC, Net Benefit). It also includes multivariable simulators to estimate performance when combining multiple predictors, as well as sample size calculators for training models.
Much like how power analysis tools (such as G*Power) help researchers plan for statistical significance, E2P Simulator helps plan for practical significance, enabling more informed research decisions and efficient resource allocation in precision medicine/psychiatry and other fields focused on predictive modeling and personalization.