Bayesian inference for cluster-randomized trials with multivariate outcomes subject to both truncation by death and missingness
同时存在死亡截断与缺失的多元结局整群随机试验贝叶斯推断
Cluster-randomized trials (CRTs) on fragile populations frequently encounter complex attrition problems where the reasons for missing outcomes can be heterogeneous, with participants who are known alive, known to have died, or with unknown survival status, and with complex and distinct missing data mechanisms for each group. Although existing methods have been developed to address death truncation in CRTs, no existing methods can jointly accommodate participants who drop out…