Web Survey Bibliography
Relevance & Research Question: This presentation examines how including offline households (households without access to the internet) in a probability-based online panel counters the problem of undercoverage which online surveys are prone to. Taking into account coverage error is a central issue when conducting a survey which aims to be representative for the general population.
Methods & Data: We use data from the recruitment and first 8 waves of the German Internet Panel (GIP), a longitudinal internet survey run by the University of Mannheim. The GIP is based on a probability sample of individuals living in private households. The recruitment was done offline by short face-to-face interviews in 2012. All offline households were offered a simple PC and a 3G internet connection.
In a first step we use data from the recruitment interview to visualize the differences between respondents with and without internet. In a second step we compare online panel registration rates between those two groups. To evaluate the impact of the participation of offline households on sample representativeness we compare the panel composition with and without offline households to the German entire population. We use German Census data as benchmark for this comparison. Using longitudinal data of the GIP we analyze differences in participation and attrition rates between online and offline households over time.
Results: Analyses show that offline and online households differ in several aspects from each other. People without internet are older, more often female, more often low and medium educated and life more often in single households. These results illustrate the coverage error which is usually connected to online surveys. Sign up rates to the panel are considerably lower for offline households (15%) compared to online households (50%). However, we can show that adding these people to the panel improves sample representativeness with respect to the variables (age and gender) we compared.
Added Value: Researchers and practitioners will learn about the benefits and quirks of our approach to counter noncoverage of non-internet households in an online survey.
Web survey bibliography - General Online Research Conference (GOR) 2014 (29)
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Offline Households in the German Internet Panel; 2014; Bossert, D., Holthausen, A., Krieger, U.
- Which fieldwork method for what target group? How to improve response rate and data quality; 2014; Wulfert, T., Woppmann, A.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- Evaluating mixed-mode redesign strategies against benchmark surveys: the case of the Crime Victimization...; 2014; Klausch, L. T., Hox, J., Schouten, B.
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Social Media and Surveys: Collaboration, Not Competition; 2014; Couper, M. P.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- Increasing data quality in online surveys 4.1; 2014; Hoeckel, H.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- Online Surveys as a Management Tool for Monitoring Multicultual Virtual Team Processes; 2014; Scovotti, C.
- How much is shorter CAWI questionnaire VS CATI questionnaire?; 2014; Bartoli, B.
- WEBDATANET: A Network on Web-based Data Collection, Methodological Challenges, Solutions, and Implementation...; 2014; Tijdens, K. G., Steinmetz, S., de Pedraza, P., Serrano, F.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Incentives on demand in a probability-based online panel: redemption and the choice between pay-out...; 2014; Schaurer, I., Struminskaya, B., Kaczmirek, L.
- The Effect of De-Contextualisation - A Comparison of Response Behaviour in Self-Administered Surveys; 2014; Wetzelhuetter, D.
- Responsive designed web surveys; 2014; Dreyer, M., Reich, M., Schwarzkopf, K.
- Extra incentives for extra efforts – impact of incentives for burdensome tasks within an incentivized...; 2014; Schreier, J. H., Biethahn, N., Drewes, F.
- Students First Choice – the influence of mobile mode on results; 2014; Maxl, E.
- Device Effects: How different screen sizes affect answer quality in online questionnaires; 2014; Fischer, B., Bernet, F.
- Moving towards mobile ready web panels; 2014; Wijnant, A., de Bruijne, M.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Mixed-devices in a probability based panel survey. Effects on survey measurement error; 2014; Toepoel, V., Lugtig, P. J.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.