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Evaluating a sequential tree-based procedure for multivariate imputation of complex missing data structures

Borgoni, Riccardo and Berrington, Ann (2011) Evaluating a sequential tree-based procedure for multivariate imputation of complex missing data structures Quality and Quantity (doi:10.1007/s11135-011-9638-3).

Record type: Article


Item nonresponse in survey data can pose significant problems for social scientists carrying out statistical modeling using a large number of explanatory variables. A number of imputation methods exist but many only deal with univariate imputation, or relatively simple cases of multivariate imputation, often assuming a monotone pattern of missingness. In this paper we evaluate a tree-based approach for multivariate imputation using real data from the 1970 British Cohort Study, known for its complex pattern of nonresponse. The performance of this tree-based approach is compared to mode imputation and a sequential regression based approach within a simulation study.

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e-pub ahead of print date: December 2011
Keywords: missing data, sequential imputation, classification tree, 1970 british birth cohort
Organisations: Social Statistics & Demography


Local EPrints ID: 201035
ISSN: 0033-5177
PURE UUID: 6eb9e626-833b-4a6d-9e28-fc4d3e7b48fc

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Date deposited: 27 Oct 2011 13:41
Last modified: 18 Jul 2017 11:13

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Author: Riccardo Borgoni
Author: Ann Berrington

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