(Online) panels in times of COVID-19 |
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| Session Organisers |
Anne Conolly (NatCen Social Research) Gerry Nicolaas Peter Cornick |
| Time | Friday 9 July, 15:00 - 16:30 |
Dr Ulrich Krieger (SFB 884, University Mannheim) - Presenting Author
Dr Carina Cornesse (SFB 884, University Mannheim)
Miss The the MCS research group (SFB 884, University Mannheim)
The outbreak of COVID-19 has sparked a sudden demand for fast, frequent, and accurate data on the societal impact of the pandemic. To meet this demand quickly and efficiently, within days of the first containment measures in Germany in March 2020, 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). In a team effort, our research group was able to inform political decision makers and the general public with key information to understand the social and economic developments from as early as March 2020 as well as advance social scientific knowledge through in-depth interdisciplinary research.
This presentation gives insights into the MCS methodology and study design. We will provide a detailed account of how we adapted the GIP to create the MCS and describe the daily data collection, processing, and communication routines that were the cornerstones of our MCS methodology. In addition, we will provide insights into the necessary preconditions that allowed us to react so quickly and set up the MCS so early in the pandemic. Furthermore, we will discuss the quality of the MCS data in terms of the development of response rates as well as sample representativeness across the course of the MCS study period.
Dr Carina Cornesse (University of Mannheim) - Presenting Author
Dr Ulrich Krieger (University of Mannheim)
Ms Sabine Friedel (University of Mannheim)
Ms Marina Fikel (University of Mannheim)
Mr Tobias Rettig (University of Mannheim)
Dr Alexander Wenz (University of Mannheim)
Professor Annelies Blom (University of Mannheim)
The outbreak of COVID-19 has sparked a sudden demand for fast, frequent, and accurate data on the societal impact of the pandemic. At the onset of the pandemic, our interdisciplinary research group at the University of Mannheim therefore 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). In a team effort, our research group was able to inform political decision makers and the general public with key information to understand the social and economic developments from as early as March 2020 as well as advance social scientific knowledge through in-depth interdisciplinary research.
This presentation gives insights into the most compelling findings from the MCS. In particular, we will show how our daily data collection allowed us to explore societal developments that were so fast that they might have been missed entirely with less frequent data collection. Moreover, we will demonstrate the manifold possibilities for augmenting the MCS data with data from other sources. For example, we will show how the data gathered in the GIP prior to the pandemic provided us with important information on how the MCS respondents’ lives changed as a result of the pandemic. Furthermore, we will show how we gained insights into the association between the changes in people’s lives and the epidemiological development of the pandemic by linking the MCS survey estimates to official COVID-19 statistics.
Mrs Lisa Ecke (Karlsruhe Institute of Technology) - Presenting Author
Dr Bastian Chlond (Karlsruhe Institute of Technology)
Professor Peter Vortisch (Karlsruhe Institute of Technology)
The German Mobility Panel (MOP) provides a yearly inventory of daily travel in Germany. The study is designed as a rotating panel over three consecutive years. The longitudinal panel approach allows to track the dynamics and variations in individuals’ travel behavior. Participants report their daily travel by filling in a trip diary over a period of seven consecutive days. Additionally, they report their sociodemographic characteristics in a separate questionnaire, providing information on the household level as well as on an individual level for the household members. Overall, the survey design results in a high respondent burden, thus endangering the quality and completeness of the collected data. The number of different questionnaires parallely delivered to the participants in the survey of everyday travel was unchanged since 1994. In the course of the Covid-19 pandemic, it was decided to include an additional questionnaire to the survey. The questionnaire intends to better comprehend the changes in travel behavior due to the restrictions caused by the Covid-19 pandemic. First analyses show, that although the response rate for the additional questionnaire is on a high level, the quality is quite heterogeneous. This contribution presents an analysis of how the additional questionnaire affects the data quality and survey outcomes. The analysis examines the socio-demographic characteristics of the households and the individuals who completed (or did not complete) the additional questionnaire . Further, this contribution provides an overview of how the additional information collected help to better understand the changes in travel behavior due to the Covid-19 pandemic.
Dr Michael Bergmann (Munich Center for the Economics of Aging (MEA)) - Presenting Author
Dr Salima Douhou (Munich Center for the Economics of Aging (MEA))
Dr Elena Sommer (Munich Center for the Economics of Aging (MEA))
The COVID-19 pandemic hit Europe at the beginning of 2020 and even one year later affects virtually all aspects of life – including survey research. The Survey of Health, Ageing and Retirement in Europe (SHARE) was in the middle of its Wave 8 data collection when fieldwork had to be suspended in all 28 participating countries. Against this background, SHARE, like many other surveys, put a huge amount of effort into the realization of an additional COVID-19 survey including a mode switch to telephone interviewing.
While this dataset is interesting on its own, it is even more so with regard to its utilization in combination with the wealth of existing panel data from more than 400,000 face-to-face interviews from eight waves of data collection in SHARE, including life histories of respondents. At the same time, the changes to mode and timing of data collection raises a number of important questions that have not been sufficiently answered yet: Did the suspension of Wave 8 fieldwork affect data quality with respect to the interrupted (panel) samples? What are the effects of a mode switch during an ongoing panel survey and in particular for SHARE’s specific target population of people aged 50 years and older? Are there systematic differences between respondent groups, i.e. those that participated in both the face-to-face and the telephone interview compared to those that participated only in the one or the other survey? What about mode effects, i.e. who does and who does not respond in a certain interview mode (mode selection effects) and how is a question answered in a certain interview mode (mode measurement effects)?
To answer these questions, we focus primarily on data from the eighth wave of SHARE until its suspension in March 2020 and the 1st wave of the SHARE COVID-19 Telephone Survey fielded from June to August 2020, yielding about 60,000 additional interviews. Based on these data, we analyze potential effects of the introduced changes in data collection with a particular focus on the older population and give practical advice for researchers facing similar challenges in directing their efforts. In addition, we will dive into cross-national differences in data quality as some countries only just started fieldwork, while other countries were close to rounding up fieldwork when Wave 8 data collection was suspended. Preliminary results show that the representativeness of the suspended national panel samples is better compared to the refreshment samples, which frequently have not been very advanced.