Brunton-Smith, Ian, Sturgis, Patrick 
ORCID: 0000-0003-1180-3493 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.
ISSN 0964-1998
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: | Article |
|---|---|
| Additional Information: | © 2016 The Authors |
| Divisions: | Methodology |
| Subjects: | Q Science > QA Mathematics |
| Date Deposited: | 07 Oct 2019 16:45 |
| Last Modified: | 12 Dec 2024 01:54 |
| URI: | http://eprints.lse.ac.uk/id/eprint/101907 |
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