Extension of Causal Inference - FIRCA

这项研究将主要在北京进行，北京大学的中国与张军妮合作， 博士学位是美国国立卫生研究院#R01 HL62567号资助的延伸。 在家长资助计划中，我们建议发展一套一般的统计方法，以进行因果性治疗分析 不依从性的随机激励设计研究或随机临床试验。一 在不符合规定的临床试验中，我们没有在父母拨款中考虑的另外一个问题是 “被死亡截断”。解决这个问题的传统方法忽略了一个事实，即 截断既不是“经审查的”，也不是“缺失的”，而应被视为是在扩展样本上定义的。 太空。在这次延长家长津贴的过程中，我们将讨论解决这一问题的新方案，即 我们称结果为“被死亡截断”，因为没有隐藏的结果变量的值 通过截断事件。我们将进一步将框架扩展到可能缺失的观察性研究- 数据。

This research will be done primarily in Beijing China at Peking University in collaboration with Junni Zhang, Ph.D. as an extension of NIH grant # R01 HL62567. In the parent grant, we propose to develop a general statistical methodology for causal treatment analysis of the randomized encouragement design studies or randomized clinical trials with non-compliance. One additional issue in clinical trials with non-compliance we have not considered in the parent grant is 'truncation by death". Traditional approaches addressing this issue ignore the fact that the outcome after the truncation is neither "censored" nor "missing", but should be treated as being defined on an extended sample space. In this extension of the parent grant, we will discuss a newformulation for tackling this issue, where we call the outcome "truncated by death" because there is no hidden value of the outcome variable masked by the truncating event. We will further extend the framework to observational studies with possibly missing- data.