Collider bias undermines our understanding of COVID-19 disease risk and severity
Many published studies of the current SARS-CoV-2 pandemic have analysed data from non-representative samples from populations. Here, using UK BioBank samples, Gibran Hemani and colleagues discuss the potential for such studies to suffer from collider bias, and provide suggestions for optimising stud...
Guardado en:
Autores principales: | Gareth J. Griffith, Tim T. Morris, Matthew J. Tudball, Annie Herbert, Giulia Mancano, Lindsey Pike, Gemma C. Sharp, Jonathan Sterne, Tom M. Palmer, George Davey Smith, Kate Tilling, Luisa Zuccolo, Neil M. Davies, Gibran Hemani |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2020
|
Materias: | |
Acceso en línea: | https://doaj.org/article/09f9c535f46548a4a4affd7e1fc10cce |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Gene-environment dependencies lead to collider bias in models with polygenic scores
por: Evelina T. Akimova, et al.
Publicado: (2021) -
Undermined Syncretism
por: Om Prakash
Publicado: (2011) -
When Words Collide
por: Aslam Farouk-Alli
Publicado: (2010) -
The role of forgetting in undermining good intentions.
por: Kristina R Olson, et al.
Publicado: (2013) -
Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data.
por: Ciarrah Barry, et al.
Publicado: (2021)