JSM 2005 - Toronto

Abstract #304582

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 146
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods
Abstract - #304582
Title: Mass Imputation
Author(s): Karol Krotki*+ and Darryl Creel
Companies: RTI International and RTI International
Address: 1615 M Street NW, Washington, DC, 20036, United States
Keywords: variable blocking ; sequantial imputation ; hot-deck ; education data
Abstract:

The vast majority of the large body of literature on imputation for missing data focuses on the task of imputing single variables. The challenge of imputing many variables simultaneously is less well discussed and understood. With increasing pressure on data producers to fill in "gaps" in the data rather than leaving this up to the users, the task of imputing data can translate into the need to impute literally hundreds of variables. Several ad hoc methods are known and used, but there is a need to develop a more formal treatment of this methodology. Whether the basic imputation method is deterministic or stochastic, such as hot-deck, there are principles that can be applied to make the process efficient and effective. In this paper, we outline the problems faced when doing mass imputation, suggest a series of solutions and guidelines, and discuss how some of these strategies are applied specifically in the case the 2004 National Postsecondary Student Aid Survey.

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