Publication type
Journal Article
Authors
Publication date
June 1, 2023
Summary:
Longitudinal data makes it possible to investigate change in time and its causes. While this type of data is getting more popular there is limited knowledge regarding the measurement errors involved, their stability in time and how they bias estimates of change. In this paper we apply a new method to estimate multiple types of errors concurrently, called the MultiTrait MultiError approach, to longitudinal data. This method uses a combination of experimental design and latent variable modelling to disentangle random error, social desirability, acquiescence and method effect. Using data collection from the Understanding Society Innovation Panel in the UK we investigate the stability of these measurement errors in three waves. Results show that while social desirability exhibits very high stability this is very low for method effects. Implications for social research is discussed.
Published in
Structural Equation Modeling
Volume and page numbers
Volume: 30 , p.592 -603
DOI
https://doi.org/10.1080/10705511.2022.2145961
ISSN
10705511
Subjects
Notes
Open Access
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
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