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Causal inference for continuous-time processes when covariates are observed only at discrete times

协变量仅在离散时点观测时的连续时间过程因果推断

Most of the work on the structural nested model and g-estimation for causal inference in longitudinal data assumes a discrete-time underlying data generating process. However, in some observational studies, it is more reasonable to assume that the data are generated from a continuous-time process and are only observable at discrete time points. When these circumstances arise, the sequential randomization assumption in the observed discrete-time data, which is essential in…

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Building a Stronger Instrument in an Observational Study of Perinatal Care for Premature Infants

在早产儿围产期护理观察研究中构建更强工具变量

An instrument is a random nudge toward acceptance of a treatment that affects outcomes only to the extent that it affects acceptance of the treatment. Nonetheless, in settings in which treatment assignment is mostly deliberate and not random, there may exist some essentially random nudges to accept treatment, so that use of an instrument might extract bits of random treatment assignment from a setting that is otherwise quite biased in its treatment assignments. An instrument…

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Bounds on Causal Effects in Three-Arm Trials With Non-Compliance

存在不依从的三臂试验中的因果效应界

Summary The paper considers the analysis of three-arm randomized trials with non-compliance. In these trials, the average causal effects of treatments within principal strata of compliance behaviour are of interest for better understanding the effect of the treatment. Unfortunately, even with the usual assumptions, the average causal effects of treatments within principal strata are not point identified. However, the observable data do provide useful information on the…

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