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Lookup NU author(s): Dr Nan Lin,
Dr Jian Shi,
Professor Robin Henderson
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Estimation bias arising from local model uncertainty and incomplete data has been studied by Copas & Eguchi (2005) under the assumption of a correctly specified marginal model. We extend the approach to allow additional local uncertainty in the assumed marginal model, arguing that this is almost unavoidable for nonlinear problems. We present a general bias analysis and sensitivity procedure for such doubly misspecified models and illustrate the breadth of application through three examples: logistic regression with a missing confounder, measurement error for binary responses and survival analysis with frailty. We show that a double-the-variance rule is not conservative under double misspecification. The ideas are brought together in a meta-analysis of studies of rehabilitation rates for juvenile offenders.
Author(s): Lin NX, Shi JQ, Henderson R
Publication type: Article
Publication status: Published
Print publication date: 26/02/2012
ISSN (print): 0006-3444
ISSN (electronic): 1464-3510
Publisher: Oxford University Press
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