Mediation analysis of time‐to‐event endpoints accounting for repeatedly measured mediators subject to time‐varying confounding

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 throug...

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Vydané v:	Statistics in medicine Ročník 38; číslo 24; s. 4828 - 4840
Hlavní autori:	Vansteelandt, Stijn, Linder, Martin, Vandenberghe, Sjouke, Steen, Johan, Madsen, Jesper
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Wiley Subscription Services, Inc 30.10.2019 John Wiley and Sons Inc
Predmet:	Cardiovascular Diseases - epidemiology Cardiovascular Diseases - prevention & control Confounding Factors, Epidemiologic Diabetes Mellitus, Type 2 - drug therapy Diabetic Angiopathies - epidemiology Diabetic Angiopathies - prevention & control Effect Modifier, Epidemiologic Endpoint Determination g‐formula Humans Hypoglycemic Agents - therapeutic use Liraglutide - therapeutic use longitudinal data mediation Models, Statistical path‐specific effect Randomized Controlled Trials as Topic Research Design time‐dependent confounding path-specific effect time-dependent confounding mediation g-formula longitudinal data
ISSN:	0277-6715, 1097-0258, 1097-0258
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