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Multiple Imputation When Rate of Change is the Outcome of Interest
Manisha Desai1, Aya A Mitani2, Susan W Bryson3
1Professor of Biomedical Informatics Research in the Department of Medicine, Stanford University, Stanford, CA.
Abstract:
Little research has been devoted to multiple imputation (MI) of derived variables. This study investigates various MI approaches for the outcome, rate of change, when the analysis model is a two-stage linear regression. Simulations showed that competitive approaches depended on the missing data mechanism and presence of auxiliary terms.
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