Direct Estimation for Commonly Used Pattern-Mixture Models in Clinical Trials
临床试验常用模式混合模型的直接估计
Pattern-mixture models have received increasing attention as they are commonly used to assess treatment effects in primary or sensitivity analyses for clinical trials with nonignorable missing data. Pattern-mixture models have traditionally been implemented using multiple imputation, where the variance estimation may be a challenge because the Rubin's approach of combining between- and within-imputation variance may not provide consistent variance estimation while bootstrap…