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April 2004 Missing at random, likelihood ignorability and model completeness
Guobing Lu, John B. Copas
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Ann. Statist. 32(2): 754-765 (April 2004). DOI: 10.1214/009053604000000166

Abstract

This paper provides further insight into the key concept of missing at random (MAR) in incomplete data analysis. Following the usual selection modelling approach we envisage two models with separable parameters: a model for the response of interest and a model for the missing data mechanism (MDM). If the response model is given by a complete density family, then frequentist inference from the likelihood function ignoring the MDM is valid if and only if the MDM is MAR. This necessary and sufficient condition also holds more generally for models for coarse data, such as censoring. Examples are given to show the necessity of the completeness of the underlying model for this equivalence to hold.

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Guobing Lu. John B. Copas. "Missing at random, likelihood ignorability and model completeness." Ann. Statist. 32 (2) 754 - 765, April 2004. https://doi.org/10.1214/009053604000000166

Information

Published: April 2004
First available in Project Euclid: 28 April 2004

zbMATH: 1048.62007
MathSciNet: MR2060176
Digital Object Identifier: 10.1214/009053604000000166

Subjects:
Primary: 62B99, 62F10, 62N01

Rights: Copyright © 2004 Institute of Mathematical Statistics

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Vol.32 • No. 2 • April 2004
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