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未观测混杂的平均强度敏感性分析AI 解读

Summary Sensitivity analysis for the unconfoundedness assumption is crucial in observational studies. For this purpose, the marginal sensitivity model has gained popularity in recent years owing to its good interpretability and mathematical properties. However, most existing models only consider a worst-case parameter that bounds the logit difference between the observed-data and full-data propensity scores, which may not fully capture the extent of unmeasured confounding.…

滞后与溢出处理效应的多重条件随机化检验AI 解读

Abstract We consider the problem of constructing multiple independent conditional randomization tests using a single dataset. Because the tests are independent, the randomization p-values can be interpreted individually and combined using standard methods for multiple testing. We give a simple, sequential construction of such tests and then discuss its application to three problems: Rosenbaum’s evidence factors for observational studies, lagged treatment effects in…

什么是随机化检验？AI 解读

The meaning of randomization tests has become obscure in statistics education and practice over the last century.This article makes a fresh attempt at rectifying this core concept of statistics.A new term-"quasirandomization test"-is introduced to define significance tests based on theoretical models and distinguish these tests from the "randomization tests" based on the physical act of randomization.The practical importance of this distinction is illustrated through a real…