Abstract Details
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Activity Number:
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359
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Type:
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Roundtables
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Date/Time:
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Tuesday, August 5, 2014 : 12:30 PM to 1:50 PM
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Sponsor:
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Mental Health Statistics Section
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Abstract #311071
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Title:
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Imputation for Large Cohorts
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Author(s):
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Elizabeth A. Stuart*+
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Companies:
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Johns Hopkins Bloomberg School of Public Health
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Keywords:
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Missing data ;
Multiple imputation by chained equations ;
Multiple imputation
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Abstract:
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This roundtable will discuss recent advances in multiple imputation approaches for handling missing data, with a focus on methods that can be used with large data sets. A focus will be on the popular multiple imputation by chained equations approach, which fits a series of conditional imputation models. Topics of discussion will include ensuring imputation and analysis model congeniality, imputation diagnostics, the particular complexities of creating imputations for analyses to estimate causal effects, and modifications that allow consideration of data that are not missing at random. Software resources also will be discussed, with a handout providing key references and links to common packages.
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Authors who are presenting talks have a * after their name.
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