Multiple imputation for missing ordinal data

Ling Chen, Robert F. Valois, Mariana Toma-Drane, J. Wanzer Drane

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Simulations were used to compare complete case analysis of ordinal data with including multivariate normal imputations. MVN methods of imputation were not as good as using only complete cases. Bias and standard errors were measured against coefficients estimated from logistic regression and a standard data set.

Original languageEnglish
Pages (from-to)288-299
Number of pages12
JournalJournal of Modern Applied Statistical Methods
Volume4
Issue number1
DOIs
StatePublished - May 2005

Keywords

  • Complete case analysis
  • Missing data mechanism
  • Multiple logistic regression

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