Bayesian Methods for Nonignorable Dropout in Joint Models in Smoking Cessation Studies
戒烟研究联合模型中不可忽略退出的贝叶斯方法
Inference on data with missingness can be challenging, particularly if the knowledge that a measurement was unobserved provides information about its distribution. Our work is motivated by the Commit to Quit II study, a smoking cessation trial that measured smoking status and weight change as weekly outcomes. It is expected that dropout in this study was informative and that patients with missed measurements are more likely to be smoking, even after conditioning on their…