Flexible, Free Software for Multilevel Multiple Imputation: A Review of Blimp and jomo. (October 2019)

• Record Type: Journal Article
• Authors: Hayes, Timothy
• Is Part Of: Journal of educational and behavioral statistics. Volume 44:Number 5(2019)
• Page Start: 625
• Page End: 641
• Publication Date: 2019-10
• Subjects: missing data -- multiple imputation -- multilevel modeling -- statistical software; Educational statistics -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 370.2
• DOI: 10.3102/1076998619858624
• Languages: English
• ISSNs: 1076-9986

Abstract

Multiple imputation is a popular method for addressing data that are presumed to be missing at random. To obtain accurate results, one's imputation model must be congenial to (appropriate for) one's intended analysis model. This article reviews and demonstrates two recent software packages, Blimp andjomo, to multiply impute data in a manner congenial with three prototypical multilevel modeling analyses: (1) a random intercept model, (2) a random slope model, and (3) a cross-level interaction model. Following these analysis examples, I review and discuss both software packages.