Does the Recruitment of Offline Households Increase the Sample Representativeness of Probability-Based Online Panels? Evidence From the German Internet Panel

Author:

Blom Annelies G.12,Herzing Jessica M. E.2,Cornesse Carina23,Sakshaug Joseph W.24,Krieger Ulrich2,Bossert Dayana2

Affiliation:

1. School of Social Sciences, University of Mannheim, Mannheim, Germany

2. Collaborative Research Center 884 “Political Economy of Reforms” (SFB 884), University of Mannheim, Mannheim, Germany

3. The GESIS – Leibniz Institute for the Social Sciences, Mannheim, Germany

4. University of Manchester, Manchester, UK

Abstract

The past decade has seen a rise in the use of online panels for conducting survey research. However, the popularity of online panels, largely driven by relatively low implementation costs and high rates of Internet penetration, has been met with criticisms regarding their ability to accurately represent their intended target populations. This criticism largely stems from the fact that (1) non-Internet (or offline) households, despite their relatively small size, constitute a highly selective group unaccounted for in Internet panels, and (2) the preeminent use of nonprobability-based recruitment methods likely contributes a self-selection bias that further compromises the representativeness of online panels. In response to these criticisms, some online panel studies have taken steps to recruit probability-based samples of individuals and providing them with the means to participate online. Using data from one such study, the German Internet Panel, this article investigates the impact of including offline households in the sample on the representativeness of the panel. Consistent with studies in other countries, we find that the exclusion of offline households produces significant coverage biases in online panel surveys, and the inclusion of these households in the sample improves the representativeness of the survey despite their lower propensity to respond.

Publisher

SAGE Publications

Subject

Law,Library and Information Sciences,Computer Science Applications,General Social Sciences

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