Cargando…
Detecting and correcting the bias of unmeasured factors using perturbation analysis: a data-mining approach
BACKGROUND: The randomized controlled study is the gold-standard research method in biomedicine. In contrast, the validity of a (nonrandomized) observational study is often questioned because of unknown/unmeasured factors, which may have confounding and/or effect-modifying potential. METHODS: In thi...
Autor principal: | Lee, Wen-Chung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925987/ https://www.ncbi.nlm.nih.gov/pubmed/24499374 http://dx.doi.org/10.1186/1471-2288-14-18 |
Ejemplares similares
-
Detecting a Weak Association by Testing its Multiple Perturbations: a Data Mining Approach
por: Lo, Min-Tzu, et al.
Publicado: (2014) -
Quantitative bias analysis in practice: review of software for regression with unmeasured confounding
por: Kawabata, Emily, et al.
Publicado: (2023) -
Do Measured and Unmeasured Family Factors Bias the Association Between Education and Self-Assessed Health?
por: Monden, Christiaan W. S.
Publicado: (2009) -
Assessing Techniques for Quantifying the Impact of Bias Due to an Unmeasured Confounder: An Applied Example
por: Barberio, Julie, et al.
Publicado: (2021) -
Unmeasured anions: the unknown unknowns
por: Venkatesh, Bala, et al.
Publicado: (2008)