Estimator-Aligned Prospective Sample Size Determination for Designs Using Inverse Probability of Treatment Weighting
与估计量匹配的逆概率处理加权前瞻性样本量设计
In observational studies, accurately characterizing variance is critical for sample size determination, yet unaccounted-for variability from propensity score estimation and the resulting weights limit the accuracy of standard variance approximations for design. Existing approaches often rely on heuristics or randomized controlled trial (RCT) formulas that treat weights as fixed, potentially misaligning prospective design with the causal estimator used at analysis. We propose…