Model-based inference for categorical survey data subject to non-ignorable non-response (with discussion)
Forster, Jonathan J. and Smith, Peter W.F. (1998) Model-based inference for categorical survey data subject to non-ignorable non-response (with discussion). Journal of the Royal Statistical Society: Series B (Statistical Methodology), 60, (1), 57-70. (doi:10.1111/1467-9868.00108).
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We consider non-response models for a single categorical response with categorical covariates whose values are always observed. We present Bayesian methods for ignorable models and a particular non-ignorable model, and we argue that standard methods of model comparison are inappropriate for comparing ignorable and non-ignorable models. Uncertainty about ignorability of non-response is incorporated by introducing parameters describing the extent of non-ignorability into a pattern mixture specification and integrating over the prior uncertainty associated with these parameters. Our approach is illustrated using polling data from the 1992 British general election panel survey. We suggest sample size adjustments for surveys when non-ignorable non-response is expected.
|Subjects:||Q Science > QA Mathematics
H Social Sciences > HA Statistics
|Divisions:||University Structure - Pre August 2011 > School of Mathematics > Statistics
|Date Deposited:||11 May 2007|
|Last Modified:||12 Jul 2012 06:34|
|Contributors:||Forster, Jonathan J. (Author)
Smith, Peter W.F. (Author)
|Contact Email Address:||email@example.com|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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