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

Publication type

Journal Article


Publication date

February 15, 2017


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.

Published in

Journal of the Royal Statistical Society Series A (Statistics in Society)

Volume and page numbers

Volume: 180 , p.551 -568






Open Access article

Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society.

© 2016 The Authors Journal of the Royal Statistical Society: Series A (Statistics in Society) 0964–1998/17/180000

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided that the original work is properly cited.

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