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结合秩统计量的个体处理效应分布随机化检验AI 解读

What proportion of treated units actually benefited from an experimental intervention? What is the median or the largest individual treatment effect? This paper develops methods for answering such questions about the distribution of individual causal effects in randomized experiments. Existing approaches require the analyst to select a rank-based test statistic before observing the data. A poor choice can substantially reduce power, while searching over multiple test…

用于过程追踪与其他单案例研究的 p 值AI 解读

We introduce a method for calculating \(p\)-values to test causal hypotheses in qualitative research \emph{a la} process tracing. As in an experiment, our \(p\)-value tells us how often one would make the same or more compelling observations favoring one theory while entertaining a rival theory. We adapt Fisher's (1935) randomization-based urn model to the reality of qualitative researchers, who cannot randomize history, but can make observations about historical processes.…