Estimating stochastic survey response errors using the multitrait-multierror model

Publication type

Journal Article

Authors

Publication date

January 1, 2022

Summary:

Surveys are well known to contain response errors of different types, including acquiescence, social desirability, common method variance and random error simultaneously. Nevertheless, a single error source at a time is all that most methods developed to estimate and correct for such errors consider in practice. Consequently, estimation of response errors is inefficient, their relative importance is unknown and the optimal question format may not be discoverable. To remedy this situation, we demonstrate how multiple types of errors can be estimated concurrently with the recently introduced ‘multitrait-multierror’ (MTME) approach. MTME combines the theory of design of experiments with latent variable modelling to estimate response error variances of different error types simultaneously. This allows researchers to evaluate which errors are most impactful, and aids in the discovery of optimal question formats. We apply this approach using representative data from the United Kingdom to six survey items measuring attitudes towards immigrants that are commonly used across public opinion studies.

Published in

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

Volume and page numbers

Volume: 185 , p.134 -155

DOI

https://doi.org/10.1111/rssa.12733

ISSN

09641998

Subjects

Notes

Open Access

© 2021 The Authors. Journal of the Royal Statistical Society: Series A (Statistics in Society) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.


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