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

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

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.

Interviewer effect, Measurement error, Mixed effects location–scale model, Stat-JR software, Understanding society
0964-1998
551-568
Brunton-Smith, Ian
fdb27626-ba05-4d54-b00a-12a8c0a82db3
Sturgis, Patrick
b9f6b40c-50d2-4117-805a-577b501d0b3c
Leckie, George
f43160a2-f379-4c38-b6b3-db5235181b33
Brunton-Smith, Ian
fdb27626-ba05-4d54-b00a-12a8c0a82db3
Sturgis, Patrick
b9f6b40c-50d2-4117-805a-577b501d0b3c
Leckie, George
f43160a2-f379-4c38-b6b3-db5235181b33

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), 551-568. (doi:10.1111/rssa.12205).

Record type: Article

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.

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More information

e-pub ahead of print date: 13 May 2016
Published date: 1 February 2017
Keywords: Interviewer effect, Measurement error, Mixed effects location–scale model, Stat-JR software, Understanding society

Identifiers

Local EPrints ID: 413165
URI: https://eprints.soton.ac.uk/id/eprint/413165
ISSN: 0964-1998
PURE UUID: d9e0c4b6-c8cb-419f-a195-3e646eec8a61
ORCID for Patrick Sturgis: ORCID iD orcid.org/0000-0003-1180-3493

Catalogue record

Date deposited: 17 Aug 2017 16:30
Last modified: 14 Mar 2019 01:39

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