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

Detecting and understanding interviewer effects on survey data using a cross-classified mixed-effects location scale model
Detecting and understanding interviewer effects on survey data 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 associated with interviewer error. We illustrate this model using data from wave 3 of the UK Household Longitudinal Survey (UKHLS), 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.
0035-9238
1-39
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 (2016) Detecting and understanding interviewer effects on survey data using a cross-classified mixed-effects location scale model. Journal of the Royal Statistical Society. Series A (General), 1-39. (In Press)

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 associated with interviewer error. We illustrate this model using data from wave 3 of the UK Household Longitudinal Survey (UKHLS), 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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Accepted/In Press date: 17 March 2016
Organisations: Social Statistics & Demography

Identifiers

Local EPrints ID: 390921
URI: https://eprints.soton.ac.uk/id/eprint/390921
ISSN: 0035-9238
PURE UUID: 4e43ce7e-d453-4096-ad25-2cba91a91b15
ORCID for Patrick Sturgis: ORCID iD orcid.org/0000-0003-1180-3493

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Date deposited: 07 Apr 2016 14:26
Last modified: 15 Jan 2019 01:33

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