Measurement equivalence in probability and nonprobability online panels

Nonprobability online panels are commonly used in the social sciences as a fast and inexpensive way of collecting data in contrast to more expensive probability-based panels. Given their ubiquitous use in social science research, a great deal of research is being undertaken to assess the properties...

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Bibliographic Details
Main Authors: Blom, A.G (Author), Cernat, A. (Author), Cornesse, C. (Author), Einarsson, H. (Author), Sakshaug, J.W (Author)
Format: Article
Language:English
Published: SAGE Publications Ltd 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02174nam a2200241Ia 4500
001 10.1177-14707853221085206
008 220706s2022 CNT 000 0 und d
020 |a 14707853 (ISSN) 
245 1 0 |a Measurement equivalence in probability and nonprobability online panels 
260 0 |b SAGE Publications Ltd  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1177/14707853221085206 
520 3 |a Nonprobability online panels are commonly used in the social sciences as a fast and inexpensive way of collecting data in contrast to more expensive probability-based panels. Given their ubiquitous use in social science research, a great deal of research is being undertaken to assess the properties of nonprobability panels relative to probability ones. Much of this research focuses on selection bias, however, there is considerably less research assessing the comparability (or equivalence) of measurements collected from respondents in nonprobability and probability panels. This article contributes to addressing this research gap by testing whether measurement equivalence holds between multiple probability and nonprobability online panels in Australia and Germany. Using equivalence testing in the Confirmatory Factor Analysis framework, we assessed measurement equivalence in six multi-item scales (three in each country). We found significant measurement differences between probability and nonprobability panels and within them, even after weighting by demographic variables. These results suggest that combining or comparing multi-item scale data from different sources should be done with caution. We conclude with a discussion of the possible causes of these findings, their implications for survey research, and some guidance for data users. © The Author(s) 2022. 
650 0 4 |a confirmatory factor analysis 
650 0 4 |a latent variables 
650 0 4 |a multi-item scales 
650 0 4 |a panel vendors 
650 0 4 |a web surveys 
700 1 |a Blom, A.G.  |e author 
700 1 |a Cernat, A.  |e author 
700 1 |a Cornesse, C.  |e author 
700 1 |a Einarsson, H.  |e author 
700 1 |a Sakshaug, J.W.  |e author 
773 |t International Journal of Market Research