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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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| Publicado no: | Epidemiology |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Lippincott Williams & Wilkins
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7523582/ https://ncbi.nlm.nih.gov/pubmed/32826524 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/EDE.0000000000001239 |
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