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 & Quantity (doi:10.1007/s11135-011-9638-3).

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Description/Abstract

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.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1007/s11135-011-9638-3
ISSNs: 0033-5177 (print)
Keywords: missing data, sequential imputation, classification tree, 1970 british birth cohort
Subjects:
Organisations: Social Statistics & Demography
ePrint ID: 201035
Date :
Date Event
December 2011e-pub ahead of print
Date Deposited: 27 Oct 2011 13:41
Last Modified: 18 Apr 2017 01:24
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/201035

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