THE EFFECT OF DIFFERENT EFFECT SIZE ASSUMPTIONS ON SAMPLE SIZE AND POWER: AN R-BASED APPROACH FOR CLINICAL RESEARCH
Introduction: In clinical research, sample size and power are usually calculated from closed-form analytic formulas based on a single assumed effect size. This study maps where analytic and Monte Carlo simulation power converge and diverge across clinical designs, and compares assurance (expected power) with classical...