Quantitative Bias Analysis for a Misclassified Confounder: A Comparison Between Marginal Structural Models and Conditional Models for Point Treatments

Observational data are increasingly used with the aim of estimating causal effects of treatments, through careful control for confounding. Marginal structural models estimated using inverse probability weighting (MSMs-IPW), like other methods to control for confounding, assume that confounding varia...

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Detalles Bibliográficos
Autores principales: Nab, Linda, Groenwold, Rolf H. H., van Smeden, Maarten, Keogh, Ruth H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2020
Materias:
Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523582/
https://www.ncbi.nlm.nih.gov/pubmed/32826524
http://dx.doi.org/10.1097/EDE.0000000000001239

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523582/
https://www.ncbi.nlm.nih.gov/pubmed/32826524
http://dx.doi.org/10.1097/EDE.0000000000001239

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