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Robust Inference on the Causal Effects of Stochastic Interventions under Two-Phase Sampling, with Applications in Vaccine Efficacy Trials: Much of the focus of statistical causal inference has been devoted to assessing the effects of static interventions, which specify a fixed contrast of counterfactual intervention values to evaluate a given causal effect.
While the challenge of implementing and evaluating static interventions in dynamic contexts has been considered (94– 97), we encountered similar tensions during intervention design.
In the process, we learned several important lessons related to the scope of the intervention and necessary compromises, the tension between static interventions and dynamic contexts, and the challenges of rigorously designing a behaviour change intervention for low-resource settings.
We note that designs that are better suited to the evaluation of clearly defined and static interventions may be adopted without giving sufficient attention to the challenges associated with the dynamic nature of improvement interventions and their interactions with contextual factors.
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That solution is not practical because it needs direct static intervention with each group change.
The distribution of total cost associated with the adaptive intervention simulations (Figure 7) is essentially equivalent to the distribution of costs achieved under static intervention with perfect information (Figure 5), indicating that even the short period of data collection prior to action produces parameter estimates that are sufficient for accurate prediction of the disease dynamics.
Muir et al. (1999) also reported that a 4 × 30 s passive static stretch intervention did not negatively affect the resistive torque of the plantar flexors.
Beckett et al. (2009) indicated that the repeated sprint ability was negatively affected by an interim static stretching intervention with a total duration of ~4 min.
In another study (Young and Elliott 2001) showed that a 3 × 15 s static stretching intervention of the lower extremities was able to induce a decrease in the drop jump performance but not on the concentric explosive muscle performance.
In static computer-tailored interventions, only one assessment at the beginning of the intervention is used.
Caring is not a passive, static set of interventions occurring in isolation and without a strong connection to the context in which it occurs.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com