Abstract #301777

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JSM 2003 Abstract #301777
Activity Number: 272
Type: Invited
Date/Time: Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor: WNAR
Abstract - #301777
Title: Two-stage Multiple Imputation
Author(s): Ofer Harel*+ and Joseph L. Schafer
Companies: Pennsylvania State University and Pennsylvania State University
Address: 326 Thomas Bldg., University Park, PA, 16802-2111,
Keywords: missing data ; missing at random ; ignorability
Abstract:

Conventional multiple imputation (MI) replaces the missing values in a dataset by m>1 sets of simulated values. We explore a two-stage extension of MI in which the missing data are partitioned into two parts and imputed N=mn times in a nested fashion. Two-stage MI divides the missing information into two components of variability, lending insight when the missing values are of two qualitatively different types. Point estimates and standard errors from the N complete-data analyses are consolidated by simple rules derived by analogy to nested analysis of variance. We present simple examples of two-stage MI and discuss a variety of potential applications. We also clarify the inferential role of the missingness indicators, extending Rubin's concept of ignorability to accommodate two types of missing values.

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