The University of Southampton
University of Southampton Institutional Repository

Model-based inference for categorical survey data subject to non-ignorable non-response (with discussion)

Record type: Article

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.

Full text not available from this repository.

Citation

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), pp. 57-70. (doi:10.1111/1467-9868.00108).

More information

Published date: 1998
Organisations: Statistics

Identifiers

Local EPrints ID: 29956
URI: http://eprints.soton.ac.uk/id/eprint/29956
ISSN: 1369-7412
PURE UUID: ab0edf95-96a4-4217-a842-ffb25c46c62a
ORCID for Peter W.F. Smith: ORCID iD orcid.org/0000-0003-4423-5410

Catalogue record

Date deposited: 11 May 2007
Last modified: 17 Jul 2017 15:56

Export record

Altmetrics

Contributors

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×