Evaluating a sequential tree-based procedure for multivariate imputation of complex missing data structures |
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Authors: | Riccardo Borgoni Ann Berrington |
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Affiliation: | 1. Department of Statistics, University of Milano-Bicocca, Milan, Italy 2. Division of Social Statistics, Southampton Statistical Sciences Research Institute, University of Southampton, Southampton, UK
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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. |
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