Mediation analysis for a survival outcome with time-varying exposures, mediators, and confounders.
We propose an approach to conduct mediation analysis for survival data with time-varying exposures, mediators, and confounders. We identify certain interventional direct and indirect effects through a survival mediational g-formula and describe the required assumptions. We also provide a feasible pa...
| Publicado en: | Statistics in Medicine Vol. 36; no. 18 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
8/15/2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=124646299&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 124646299 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02776715 2DZ jtl: Statistics in Medicine issn: 02776715 maglogo: Y pubinfo: dt: 8/15/2017 vid: 36 iid: 18 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 124646299 124646299 NLM28809051 124646299 10.1002/sim.7426 NLM28809051 124646299 ppct: 1 formats: tig: atl: Mediation analysis for a survival outcome with time-varying exposures, mediators, and confounders. aug: au: Lin, Sheng-Hsuan Young, Jessica G Logan, Roger VanderWeele, Tyler J affil: Department of Biostatistics, Columbia Mailman School of Public Health, New York, NY, USA sug: subj: Confounding Variable Prospective Studies Survival Analysis Environmental Exposure Adverse Effects Coronary Arteriosclerosis Mortality Algorithms Risk Factors Models, Statistical Coronary Arteriosclerosis Epidemiology Smoking Human ab: We propose an approach to conduct mediation analysis for survival data with time-varying exposures, mediators, and confounders. We identify certain interventional direct and indirect effects through a survival mediational g-formula and describe the required assumptions. We also provide a feasible parametric approach along with an algorithm and software to estimate these effects. We apply this method to analyze the Framingham Heart Study data to investigate the causal mechanism of smoking on mortality through coronary artery disease. The estimated overall 10-year all-cause mortality risk difference comparing "always smoke 30 cigarettes per day" versus "never smoke" was 4.3 (95% CI = (1.37, 6.30)). Of the overall effect, we estimated 7.91% (95% CI: = 1.36%, 19.32%) was mediated by the incidence and timing of coronary artery disease. The survival mediational g-formula constitutes a powerful tool for conducting mediation analysis with longitudinal data. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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