Appropriate inclusion of interactions was needed to avoid bias in multiple imputation

OBJECTIVE: Missing data are a pervasive problem, often leading to bias in complete records analysis (CRA). Multiple imputation (MI) via chained equations is one solution, but its use in the presence of interactions is not straightforward. STUDY DESIGN AND SETTING: We simulated data with outcome Y de...

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Detalles Bibliográficos
Autores principales: Tilling, Kate, Williamson, Elizabeth J., Spratt, Michael, Sterne, Jonathan A.C., Carpenter, James R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176003/
https://www.ncbi.nlm.nih.gov/pubmed/27445178
http://dx.doi.org/10.1016/j.jclinepi.2016.07.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176003/
https://www.ncbi.nlm.nih.gov/pubmed/27445178
http://dx.doi.org/10.1016/j.jclinepi.2016.07.004

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