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Activity Number: 405
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
Sponsor: Survey Research Methods Section
Abstract #312731 View Presentation
Title: Predictive Ratio Matching Imputation of Nested Compositional Data with Semicontinuous Variables
Author(s): Gerko Vink*+ and Jeroen Pannekoek and Stef Van Buuren
Companies: Utrecht University and Statistics Netherlands and Utrecht University
Keywords: Compositional data ; Multiple Imputation ; Predictive Ratio Matching ; Semicontinuous data ; Imputation ; Restrictions
Abstract:

Imputing compositional data is challenging because imputations must obey the restrictions in the data while remaining strictly non-negative. This problem becomes increasingly complicated when the data has a nested compositional structure. We propose predictive ratio matching (PRM) as a general imputation method for compositional data. PRM imputes (nested) compositional data by iteratively updating the pairwise ratios in the data. The proposed method yields plausible inference and imputations, while keeping the intricate compositional structure, data distributions and relations intact.


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