Combining Multiple Imputation and Inverse‐Probability Weighting

Two approaches commonly used to deal with missing data are multiple imputation (MI) and inverse‐probability weighting (IPW). IPW is also used to adjust for unequal sampling fractions. MI is generally more efficient than IPW but more complex. Whereas IPW requires only a model for the probability that...

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Veröffentlicht in:	Biometrics 2012-03, Vol.68 (1), p.129-137
Hauptverfasser:	Seaman, Shaun R., White, Ian R., Copas, Andrew J., Li, Leah
Format:	Artikel
Sprache:	eng
Schlagworte:	1958 British Birth Cohort Bias BIOMETRIC METHODOLOGY Biometrics biometry Biometry - methods child development cohort studies Data imputation Data Interpretation, Statistical Datasets Estimation bias Estimators Estimators for the mean Gestational age Inverse problems linear models Marginal model Missing at random Missing data Modeling Probability Sample Size Statistical variance Survey weighting Term weighting variance Variance analysis
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