Abstract #300702

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JSM 2002 Abstract #300702
Activity Number: 384
Type: Contributed
Date/Time: Thursday, August 15, 2002 : 8:30 AM to 10:20 AM
Sponsor: General Methodology
Abstract - #300702
Title: Two-stage Multiple Imputation
Author(s): Ofer Harel*+ and Joseph Schafer
Affiliation(s): Pennsylvania State University and Pennsylvania State University
Address: 326 Thomas Bldg., University Park, Pennsylvania, 16802, USA
Keywords: ignorability ; missing data ; missing at random
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 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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Revised March 2002