A bias‐corrected estimator in multiple imputation for missing data

Multiple imputation (MI) is one of the most popular methods to deal with missing data, and its use has been rapidly increasing in medical studies. Although MI is rather appealing in practice since it is possible to use ordinary statistical methods for a complete data set once the missing values are...

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Veröffentlicht in:	Statistics in medicine 2018-10, Vol.37 (23), p.3373-3386
Hauptverfasser:	Tomita, Hiroaki, Fujisawa, Hironori, Henmi, Masayuki
Format:	Artikel
Sprache:	eng
Schlagworte:	Cardiovascular disease density ratio kernel density estimation Methods Missing data multiple imputation Regression analysis weighted likelihood
Online-Zugang:	Volltext
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