Comparison of methods for handling covariate missingness in propensity score estimation with a binary exposure

BACKGROUND: Causal effect estimation with observational data is subject to bias due to confounding, which is often controlled for using propensity scores. One unresolved issue in propensity score estimation is how to handle missing values in covariates. METHOD: Several approaches have been proposed...

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Detalles Bibliográficos
Autores principales: Coffman, Donna L., Zhou, Jiangxiu, Cai, Xizhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318364/
https://www.ncbi.nlm.nih.gov/pubmed/32586271
http://dx.doi.org/10.1186/s12874-020-01053-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318364/
https://www.ncbi.nlm.nih.gov/pubmed/32586271
http://dx.doi.org/10.1186/s12874-020-01053-4

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