Extension of Causal Inference - FIRCA

这项研究将主要在中国北京的北京大学进行， 博士作为NIH资助#R 01 HL 62567的扩展。 在家长补助金方面，我们建议发展一套通用的统计方法，以分析 随机鼓励设计研究或随机临床试验不依从。一 我们在母基金中没有考虑的临床试验中的其他不依从性问题是 “死亡截断”。解决这一问题的传统方法忽略了这样一个事实，即 截断既不是“删失”，也不是“缺失”，但应视为在扩展样本上定义的截断 空间在这次家长补助金的扩展中，我们将讨论一个解决这个问题的新公式， 我们称结果为“因死亡而截断”，因为结果变量没有隐藏值被掩盖 被截断事件所影响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.