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When Is a Complete-Case Approach to Missing Data Valid? The Importance of Effect-Measure Modification
When estimating causal effects, careful handling of missing data is needed to avoid bias. Complete-case analysis is commonly used in epidemiologic analyses. Previous work has shown that covariate-stratified effect estimates from complete-case analysis are unbiased when missingness is independent of...
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| Publicado no: | Am J Epidemiol |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7705610/ https://ncbi.nlm.nih.gov/pubmed/32601706 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/aje/kwaa124 |
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