Multiple Imputation for Missing Data: Fully Conditional Specification Versus Multivariate Normal Imputation
نویسندگان
چکیده
منابع مشابه
Multiple imputation for missing data: fully conditional specification versus multivariate normal imputation.
Statistical analysis in epidemiologic studies is often hindered by missing data, and multiple imputation is increasingly being used to handle this problem. In a simulation study, the authors compared 2 methods for imputation that are widely available in standard software: fully conditional specification (FCS) or "chained equations" and multivariate normal imputation (MVNI). The authors created ...
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ژورنال
عنوان ژورنال: American Journal of Epidemiology
سال: 2010
ISSN: 0002-9262,1476-6256
DOI: 10.1093/aje/kwp425