Alternative approaches to multilevel modelling of survey noncontact and refusal
Alternative approaches to multilevel modelling of survey noncontact and refusal
We review three alternative approaches to modelling survey noncontact and refusal: multinomial, sequential and sample selection (bivariate probit) models. We then propose a multilevel extension of the sample selection model to allow for both interviewer effects and dependency between noncontact and refusal rates at the household and interviewer level. All methods are applied and compared in an analysis of household nonresponse in the UK, using a dataset with unusually rich information on both respondents and nonrespondents from six major surveys. After controlling for household characteristics, there is little evidence of residual correlation between the unobserved characteristics affecting noncontact and refusal propensities at either the household or the interviewer level. We also find that the estimated coefficients of the multinomial and sequential models are surprisingly similar, which further investigation via a simulation study suggests is due to there being little overlap between the predictors of noncontact and refusal.
Clustered categorical response data, discrete choice models, hierarchical models, survey nonresponse, interviewer effects.
Southampton Statistical Sciences Research Institute, University of Southampton
Steele, Fiona
7adddb2a-7213-4423-9101-9f796c15584e
Durrant, Gabriele B.
1d0c7fdb-83d1-40fe-9b42-8653f5aef4c8
7 August 2009
Steele, Fiona
7adddb2a-7213-4423-9101-9f796c15584e
Durrant, Gabriele B.
1d0c7fdb-83d1-40fe-9b42-8653f5aef4c8
Steele, Fiona and Durrant, Gabriele B.
(2009)
Alternative approaches to multilevel modelling of survey noncontact and refusal
(S3RI Methodology Working Papers, M09/15)
Southampton, UK.
Southampton Statistical Sciences Research Institute, University of Southampton
37pp.
Record type:
Monograph
(Working Paper)
Abstract
We review three alternative approaches to modelling survey noncontact and refusal: multinomial, sequential and sample selection (bivariate probit) models. We then propose a multilevel extension of the sample selection model to allow for both interviewer effects and dependency between noncontact and refusal rates at the household and interviewer level. All methods are applied and compared in an analysis of household nonresponse in the UK, using a dataset with unusually rich information on both respondents and nonrespondents from six major surveys. After controlling for household characteristics, there is little evidence of residual correlation between the unobserved characteristics affecting noncontact and refusal propensities at either the household or the interviewer level. We also find that the estimated coefficients of the multinomial and sequential models are surprisingly similar, which further investigation via a simulation study suggests is due to there being little overlap between the predictors of noncontact and refusal.
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s3ri-workingpaper-M09-15.pdf
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Published date: 7 August 2009
Keywords:
Clustered categorical response data, discrete choice models, hierarchical models, survey nonresponse, interviewer effects.
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Local EPrints ID: 67249
URI: http://eprints.soton.ac.uk/id/eprint/67249
PURE UUID: edbaab0a-e397-45d6-ba56-817a120a8e58
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Date deposited: 07 Aug 2009
Last modified: 20 Feb 2024 03:17
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Contributors
Author:
Fiona Steele
Author:
Gabriele B. Durrant
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