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Detecting and understanding interviewer effects on survey data by using a cross-classified mixed effects location-scale model

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Brunton-Smith, Ian, Sturgis, Patrick and Leckie, George (2017) Detecting and understanding interviewer effects on survey data by using a cross-classified mixed effects location-scale model. Journal of the Royal Statistical Society: Series A (Statistics in Society) , 180 (2). pp. 551-568. doi:10.1111/rssa.12205

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Official URL: http://dx.doi.org/10.1111/rssa.12205

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Abstract

We propose a cross-classified mixed effects location–scale model for the analysis of interviewer effects in survey data. The model extends the standard two-way cross-classified random-intercept model (respondents nested in interviewers crossed with areas) by specifying the residual variance to be a function of covariates and an additional interviewer random effect. This extension provides a way to study interviewers’ effects on not just the ‘location’ (mean) of respondents’ responses, but additionally on their ‘scale’ (variability). It therefore allows researchers to address new questions such as ‘Do interviewers influence the variability of their respondents’ responses in addition to their average, and if so why?’. In doing so, the model facilitates a more complete and flexible assessment of the factors that are associated with interviewer error. We illustrate this model by using data from wave 3 of the UK Household Longitudinal Survey, which we link to a range of interviewer characteristics measured in an independent survey of interviewers. By identifying both interviewer characteristics in general, but also specific interviewers who are associated with unusually high or low or homogeneous or heterogeneous responses, the model provides a way to inform improvements to survey quality.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Social Sciences > Sociology
Library of Congress Subject Headings (LCSH): Multilevel models (Statistics), Errors-in-variables models, Interviews -- Mathematical models, Interviewing -- Mathematical models
Journal or Publication Title: Journal of the Royal Statistical Society: Series A (Statistics in Society)
Publisher: Wiley-Blackwell Publishing Ltd.
ISSN: 0964-1998
Official Date: February 2017
Dates:
DateEvent
February 2017Published
13 May 2016Available
27 March 2016Accepted
Volume: 180
Number: 2
Page Range: pp. 551-568
DOI: 10.1111/rssa.12205
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
Funder: Economic and Social Research Council (Great Britain) (ESRC)
Grant number: ES/L008351/1

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