Causal Inference of Ambiguous Manipulations
Causal Inference of Ambiguous Manipulations
复制标题
模糊操纵的因果推断
DOI：
--
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
R. Scheines
中科院分区：
文献类型：
--
作者：
P. Spirtes;R. Scheines
在过去的二十年中，因果推断理论的基本框架已经形成。然而，该理论没有考虑以下问题。有时两个或多个测量变量是彼此的确定性函数，这并非有意为之，而是由于冗余测量。在这些情况下，对一个观测定义变量的操作实际上可能是对某些潜在变量操作的一种模糊描述，尽管操作者并不知道是这种情况。在本文中，我们重新审视精确描述条件和假设的问题，在这些条件和假设下，即使允许“模糊操作”的可能性，对操作效果进行可靠推断也是可能的。
Over the last two decades, a fundamental outline of a theory of causal inference has emerged. However, this theory does not consider the following problem. Sometimes two or more measured variables are deterministic functions of one another, not deliberately, but because of redundant measurements. In these cases, manipulation of an observed defined variable may actually be an ambiguous description of a manipulation of some underlying variables, although the manipulator does not know that this is the case. In this article we revisit the question of precisely characterizing conditions and assumptions under which reliable inference about the effects of manipulations is possible, even when the possibility of “ambiguous manipulations” is allowed.