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存在未测混杂时的前门与后门调整：前门及混合调整的偏差公式与职业培训应用AI 解读

We demonstrate that the front-door adjustment can be a useful alternative to standard covariate adjustments (i.e., back-door adjustments), even when the assumptions required for the front-door approach do not hold. We do this by providing asymptotic bias formulas for the front-door approach that can be compared directly to bias formulas for the back-door approach. In some cases, this allows the tightening of bounds on treatment effects. We also show that under one-sided…

解决选举争议：投票后投票选择数据的有限检验功效AI 解读

In close elections, the losing side has an incentive to obtain evidence that the election result is incorrect. Sometimes this evidence comes in the form of court testimony from a sample of invalid voters, and this testimony is used to adjust vote totals (Borders v King County, 2005; Belcher v Mayor of Ann Arbor, 1978). However, while courts may be reluctant to make explicit findings about out-of-sample data (e.g. invalid voters that do not testify), when samples are used to…