Model-based inference for categorical survey data subject to non-ignorable non-response Export

@article{forster:smith:2002, abstract = {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.}, address = {University of Southampton, UK}, author = {Forster, Jonathan J. and Smith, Peter W. F.}, citeulike-article-id = {3757885}, citeulike-linkout-0 = {http://dx.doi.org/10.1111/1467-9868.00108}, citeulike-linkout-1 = {http://www3.interscience.wiley.com/cgi-bin/abstract/119137012/ABSTRACT}, doi = {10.1111/1467-9868.00108}, journal = {Journal of the Royal Statistical Society: Series B: Statistical Methodology}, keywords = {survey, survey\_methodology, survey\_response}, number = {1}, pages = {57--70}, posted-at = {2008-12-08 19:30:02}, priority = {2}, title = {Model-based inference for categorical survey data subject to non-ignorable non-response}, url = {http://dx.doi.org/10.1111/1467-9868.00108}, volume = {60}, year = {1998} }

TY - JOUR ID - forster:smith:2002 L3 - citeulike-article-id:3757885 N2 - 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. IS - 1 JF - Journal of the Royal Statistical Society: Series B: Statistical Methodology AD - University of Southampton, UK EP - 70 TI - Model-based inference for categorical survey data subject to non-ignorable non-response VL - 60 SP - 57 KW - survey KW - survey_methodology KW - survey_response AU - Forster, Jonathan AU - Smith, Peter PY - 1998/// UR - http://dx.doi.org/10.1111/1467-9868.00108 ER -