title: Multiple imputation by chained equations: what is it and how does it work?
abstract: Multivariate imputation by chained equations (MICE) has emerged as a principled method of dealing with missing data. Despite properties that make MICE particularly useful for large imputation procedures and advances in software development that now make it accessible to many researchers, many psychiatric researchers have not been trained in these methods and few practical resources exist to guide researchers in the implementation of this technique. This paper provides an introduction to the MICE method with a focus on practical aspects and challenges in using this method. A brief review of software programs available to implement MICE and then analyze multiply imputed data is also provided.
authors.affiliation: Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. mazur@mathematica-mpr.com
authors.forename: Melissa J
authors.initials: MJ
authors.lastname: Azur
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Stuart
authors.forename: Constantine
authors.initials: C
authors.lastname: Frangakis
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Leaf
mesh_terms: D004812:Epidemiologic Methods; D006801:Humans; D015233:Models, Statistical; D012107:Research Design