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The outbreak of COVID‐19 has sparked a sudden demand for fast, frequent and accurate data on the societal impact of the pandemic. This demand has highlighted a divide in survey data collection: Most probability‐based social surveys, which can deliver the necessary data quality to allow valid inference to the general population, are slow, infrequent and ill‐equipped to survey people during a lockdown. Most non‐probability online surveys, which can deliver large amounts of data fast, frequently and without interviewer contact, however, cannot provide the data quality needed for population inference. Well aware of this chasm in the data landscape, at the onset of the pandemic, we set up the Mannheim Corona Study (MCS), a rotating panel survey with daily data collection on the basis of the long‐standing probability‐based online panel infrastructure of the German Internet Panel (GIP). The MCS has provided academics and political decision makers with key information to understand the social and economic developments during the early phase of the pandemic. This paper describes the panel adaptation process, demonstrates the power of the MCS data on its own and when linked to other data sources, and evaluates the data quality achieved by the MCS fast‐response methodology. [ABSTRACT FROM AUTHOR]

While online panels offer numerous advantages, they are often criticized for excluding the offline population. Therefore, some probability-based online panels have developed offline population inclusion strategies. Two dominant approaches prevail: providing internet equipment and offering an alternative survey participation mode. We investigate the impact of these approaches on two probability-based online panels in Germany: the German Internet Panel, which provides members of the offline population with internet equipment, and the GESIS Panel, which offers members of the offline population to participate via postal mail surveys. In addition, we explore the impact of offering an alternative mode only to non-internet users versus also offering the alternative mode to internet users who are unwilling to provide survey data online. Albeit lower recruitment and/or panel wave participation probabilities among offliners than onliners, we find that including the offline population has a positive long-term impact on sample accuracy in both panels. In the GESIS Panel, the positive impact is particularly strong when offering the alternative participation mode to non-internet users and internet users who are unwilling to provide survey data online. [ABSTRACT FROM AUTHOR]

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This article looks into the processes and outcomes of setting up and maintaining a probability-based longitudinal online survey, which is recruited face-to-face and representative of both the online and the offline population aged 16-75 in Germany. This German Internet Panel studies political and economic attitudes and reform preferences through bimonthly longitudinal online interviews of individuals. The results presented here demonstrate that a carefully designed and implemented online panel can produce high- quality data at lower marginal costs than existing panels that operate solely in a face-to-face mode. Analyses into the representativeness of the online sample showed no major coverage or nonresponse biases. Finally, including offline households in the panel is important as it improves the representation of the older and female segments of the population. [ABSTRACT FROM AUTHOR]

Six incentive experiments were conducted in a nonprofit online panel. In each experiment, the incentive offered for participation was a cash lottery. The control group was not offered any incentive. The cash lottery was offered in two versions: Either the total payout of the lottery was mentioned, or the lottery was split into multiple prizes. Dependent measures included response and retention rates. The results of the six individual experiments were meta-analytically summarized. Cash lotteries relative to no incentives did not reliably increase response or retention; neither did it make a significant difference if one large prize or multiple smaller prizes were raffled. [ABSTRACT FROM AUTHOR]