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In this article, we will present statistical methods to assess to what extent the effect of a randomised treatment (versus control) on a time-to-event endpoint might be explained by the effect of treatment on a mediator of interest, a variable that is measured longitudinally at planned visits throughout the trial. In particular, we will show how to identify and infer the path-specific effect of treatment on the event time via the repeatedly measured mediator levels. The considered proposal addresses complications due to patients dying before the mediator is assessed, due to the mediator being repeatedly measured, and due to posttreatment confounding of the effect of the mediator by other mediators. We illustrate the method by an application to data from the LEADER cardiovascular outcomes trial.
This article was published in the following journal.
Name: Statistics in medicine
The goal of this paper is to describe approaches for the joint analysis of repeatedly measured data with time-to-event endpoints, first separately and then in the framework of a single comprehensive m...
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A measure of the total greenhouse gas emissions produced by an individual, organization, event, or product. It is measured in units of equivalent kilograms of CARBON DIOXIDE generated in a given time frame.
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A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function.
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Exercises in which muscles are repeatedly and rapidly stretched, followed by shortening, concentric MUSCLE CONTRACTION (e.g. jumping and rebounding). They are designed to exert maximal force in minimal time by increasing STRETCH REFLEX.
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