Missing data analysis using multiple imputation: getting to the heart of the matter.
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ABSTRACT:
SUBMITTER: He Y
PROVIDER: S-EPMC2818781 | biostudies-literature | 2010 Jan
REPOSITORIES: biostudies-literature
Publications
Missing data analysis using multiple imputation: getting to the heart of the matter.
Circulation. Cardiovascular quality and outcomes 20100101 1
Missing data are a pervasive problem in health investigations. We describe some background of missing data analysis and criticize ad hoc methods that are prone to serious problems. We then focus on multiple imputation, in which missing cases are first filled in by several sets of plausible values to create multiple completed datasets, then standard complete-data procedures are applied to each completed dataset, and finally the multiple sets of results are combined to yield a single inference. We ...[more]
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