Search

This special issue is devoted to discussion of probability-based survey panels that collect data either solely or partly through online questionnaires. Panels of this kind have been around for a long time, though they have been few in number, but recent years have seen several new panels start up in Europe. This has led to renewed interest in the methodology of such panels and also to deeper questioning of the role of these panels. On one hand, the probability-based panels are to some extent competing against cheaper non-probability access panels. On the other hand, the probability-based panels are increasingly being seen as possible alternatives to more expensive probability-based survey methods. In both cases, clients and data users want to better understand the relative advantages and disadvantages of the probability-based panels. [ABSTRACT FROM AUTHOR]

Inferential statistics teach us that we need a random probability sample to infer from a sample to the general population. In online survey research, however, volunteer access panels, in which respondents self-select themselves into the sample, dominate the landscape. Such panels are attractive due to their low costs. Nevertheless, recent years have seen increasing numbers of debates about the quality, in particular about errors in the representativeness and measurement, of such panels. In this article, we describe four probability-based online and mixed-mode panels for the general population, namely, the Longitudinal Internet Studies for the Social Sciences (LISS) Panel in the Netherlands, the German Internet Panel (GIP) and the GESIS Panel in Germany, and the Longitudinal Study by Internet for the Social Sciences (ELIPSS) Panel in France. We compare them in terms of sampling strategies, offline recruitment procedures, and panel characteristics. Our aim is to provide an overview to the scientific community of the availability of such data sources to demonstrate the potential strategies for recruiting and maintaining probability-based online panels to practitioners and to direct analysts of the comparative data collected across these panels to methodological differences that may affect comparative estimates. [ABSTRACT FROM AUTHOR]