Selection bias and competing risk.
The article focuses on the advancements in understanding selection bias, particularly in the context of genetic studies and competing risks related to age at death. It highlights how selection bias can arise when individuals who have died before recruitment are excluded from studies, potentially lea...
| Publicado en: | American Journal of Epidemiology Vol. 194; no. 11; pp. 3396 - 3398 |
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| Autor principal: | |
| Formato: | letter tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Nov2025
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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=189501682&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189501682 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00029262 1X1 jtl: American Journal of Epidemiology issn: 00029262 maglogo: N pubinfo: dt: Nov2025 vid: 194 iid: 11 pid: 622 pub: Oxford University Press / USA artinfo: ui: 189501682 189501682 189501682 10.1093/aje/kwaf174 189501682 ppf: 3396 ppct: 2 formats: tig: atl: Selection bias and competing risk. aug: au: Schooling, C Mary affil: Li Ka Shing Faculty of Medicine, School of Public Health, CUNY Graduate School of Public Health and Health Policy, The University of Hong Kong, Pokfulam, Hong Kong sug: subj: Selection Bias Epidemiological Research Research Subject Recruitment Death Age Factors Mendelian Randomization ab: The article focuses on the advancements in understanding selection bias, particularly in the context of genetic studies and competing risks related to age at death. It highlights how selection bias can arise when individuals who have died before recruitment are excluded from studies, potentially leading to statistical errors and affecting causal inferences. The article also discusses the significance of disease-specific age at death patterns, illustrated with data from the United States in 2019, to better interpret studies involving long-term exposures and interventions. It emphasizes the need for precise information to mitigate biases and contextualize findings related to survival and disease outcomes. pubtype: Academic Journal doctype: letter tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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