Open AccessMultiple imputation by chained equations: what is it and how does it work?
Author(s) -
Azur Melissa J.,
Stuart Elizabeth A.,
Frangakis Constantine,
Leaf Philip J.
Publication year - 2011
Publication title -
international journal of methods in psychiatric research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.275
H-Index - 73
eISSN - 1557-0657
pISSN - 1049-8931
DOI - 10.1002/mpr.329
Subject(s) - imputation (statistics) , missing data , computer science , software , multivariate statistics , data science , data mining , machine learning , programming language
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. Copyright © 2011 John Wiley & Sons, Ltd .