Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project

Modeling multi-level survival data in multi-center epidemiological cohort studies: Applications from the ELAPSE project

Background: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cereb...

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Main Authors: Evangelia Samoli, Sophia Rodopoulou, Ulla A. Hvidtfeldt, Kathrin Wolf, Massimo Stafoggia, Bert Brunekreef, Maciej Strak, Jie Chen, Zorana J. Andersen, Richard Atkinson, Mariska Bauwelinck, Tom Bellander, Jørgen Brandt, Giulia Cesaroni, Francesco Forastiere, Daniela Fecht, John Gulliver, Ole Hertel, Barbara Hoffmann, Kees de Hoogh, Nicole A.H. Janssen, Matthias Ketzel, Jochem O. Klompmaker, Shuo Liu, Petter Ljungman, Gabriele Nagel, Bente Oftedal, Göran Pershagen, Annette Peters, Ole Raaschou-Nielsen, Matteo Renzi, Doris T. Kristoffersen, Gianluca Severi, Torben Sigsgaard, Danielle Vienneau, Gudrun Weinmayr, Gerard Hoek, Klea Katsouyanni
Format: Article
Language:English
Published: Elsevier 2021-02-01
Series:Environment International
Subjects:
Air pollution
Cox model
Frailty models
Health effects
Mixed models
Multi-level analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S0160412020323254

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http://www.sciencedirect.com/science/article/pii/S0160412020323254

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