Publication:
Analysis of Incomplete Survey Data : Multiple Imputation via Bayesian Bootstrap Predictive Mean Matching

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Date
2009
Authors
Koller-Meinfelder, Florian
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opus
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Abstract
Multiple Imputation (MI) is a general purpose approach to impute partially incomplete data. The proposed method - Bayesian Bootstrap Predictive Mean Matching - is a variant that incorporates the robustifying properties of a nearest neighbour technique (Predictive Mean Matching) into MI.
Multiple Imputation (MI) ist ein allgemeiner Ansatz zur Ergänzung fehlender Daten. Die vorgestellte Methode - Bayesian Bootstrap Predictive Mean Matching - ist eine MI-Variante, welche die robustifizierenden Eigenschaften eines Nearest-Neighbour-Verfahrens (Predictive Mean Matching) integriert.
Description
Bamberg, Univ., Diss., 2009
Keywords
Datenergänzung , Multiple Imputation, missing data , multiple imputation , nearest neighbour matching, Datenergänzung, Multiple Imputation, missing data, multiple imputation, nearest neighbour matching
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