This entry is concerned with assessing the effect of treatments that vary in time on the outcomes for individual patients. For example, levels of compliance with therapy may vary over time among participants in a clinical trial. Assessment of treatment effects in this situation is complicated by ...
Hern$'$n M. and Robins J. Causal Inference: What If. 这一章介绍了如何估计time-varying 下的causal effect. 21.1 The g-formula for time-varying treatments 求静态的$\
文章目录 19.1 The causal effect of time-varying treatments 19.2 Treatment strategies 19.3 Sequentially randomized experiments 19.4 Sequential exchangeability 19.5 Identifiability under some but not all tr... 查看原文 基于块对应的时变体数据挖掘的统一框架 ...
This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal ...
Background: Extremely low frequency (ELF) magnetic fields have been considered by researchers as a noninvasive treatment approach. Citing documented biological effects of ELF magnetic fields in recent studies, we investigate the effect of low intensity ELF magnetic field on the treatment of invasive ...
Such an effect can be more evidently seen with the subsequent ‘1’ signal (the reference pulse), as there was almost no peak in the DUT. Therefore, in this case, the effective number of SET pulses applied to the DUT was only two (the first and second ‘1’ among the total three ...
Spiking global energy prices make it all the more important to understand the distributional effects of commonly used energy transition policies such as financially-based demand management. We examine how building energy efficiency impacts the effect of time-of-use rates; peak prices could differently ...
A similar time-dependent heterogeneity of treatment effect was observed in the aggregate study meta-analysis as in the IPD pooled analysis. Treatment with BVS compared with EES cumulative through 3 years and 5 years resulted in greater rates of composite TLF and POCE, owing to increased rates ...
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The red dashed horizontal line is the average treatment effect. The ATT and QTT become smaller when ignoring the changes in qualification status than they would be when considering these changes. For example, the result with all types of households (in-stayers, in-movers, out-stayers, and ...