Canonical Causal Diagrams to Guide the Treatment of Missing Data in Epidemiologic Studies

Abstract With incomplete data, the “missing at random” (MAR) assumption is widely understood to enable unbiased estimation with appropriate methods. While the need to assess the plausibility of MAR and to perform sensitivity analyses considering “missing not at random” (MNAR) scenarios has been emph...

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Veröffentlicht in:	American journal of epidemiology 2018-12, Vol.187 (12), p.2705-2715
Hauptverfasser:	Moreno-Betancur, Margarita, Lee, Katherine J, Leacy, Finbarr P, White, Ian R, Simpson, Julie A, Carlin, John B
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Correlation analysis Data Interpretation, Statistical Epidemiologic Methods Epidemiology Exposure Graph theory Humans Longitudinal Studies Missing data Practice of Epidemiology Sensitivity analysis
Online-Zugang:	Volltext
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