REALCOM-IMPUTE software for multilevel multiple imputation with mixed response types

Harvey Goldstein

Research output: Contribution to journalArticle (Academic Journal)peer-review

101 Citations (Scopus)
421 Downloads (Pure)

Abstract

Multiple imputation is becoming increasingly established as the leading practical approach to modelling partially observed data, under the assumption that the data are missing at random. However, many medical and social datasets are multilevel, and this structure should be reected not only in the model of interest, but also in the imputation model. In particular, the imputation model should re
ect the dierences between level 1 variables and level 2 variables (which are constant across level 1 units). This led us to develop the REALCOM-IMPUTE software, which we describe in this article. This software performs multilevel multiple imputation, and handles ordinal and unordered categorical
data appropriately. It is freely available on-line, and may be used either as a standalone package, or in conjunction with the multilevel software MLwiN or Stata.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalJournal of Statistical Software
Volume45
Issue number5
Publication statusPublished - 2011

Keywords

  • multilevel multiple imputation, missing data, mixed response types.

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