Web Survey Bibliography
Title Propensity score weighting in a web-based panel survey: Comparing the effects on attrition biases in attitudinal, behavioral, and socio-demographic variables
Author Gummer, T.; Rossmann, J.
Year 2016
Access date 29.04.2016
Presentation PDF (1.02MB)
Abstract
Relevance & Research Question: Propensity score weighting (PSW) is frequently used to correct for attrition biases in panel surveys. While there is a rich methodological literature on the logic of PSW and studies on its practical application, we face a lack of in-depth discussion on the effects of using PSW to correct for attrition biases in attitudinal, behavioral, and socio-demographic variables. Consequently, we address the questions, first, whether there are differences in attrition biases between different types of variables and, second, whether we can identify patterns in the effects of applying PSW across these types of variables.
Methods & Data: Our analysis draws on data from a seven-wave web-based split-panel survey conducted during the campaign to the 2013 German federal election. The panel is supplemented with cross-sectional surveys that are comparable in terms of sampling and questionnaire. We use these cross-sections to assess attrition biases in the corresponding waves of the panel survey. The propensity score weights are calculated using the predicted propensity of respondents to participate in consecutive panel waves. The estimation of the response propensities draws on the data from the first panel wave. We assess the effect of applying these weights on attrition bias in 48 attitudinal, 38 behavioral, and 27 socio-demographic variables.
Results: Our results show that PSW successfully reduced biases in 72 out of the 113 variables. However, looking at the three types of variables, we find the rate of success to be lowest for behavioral variables compared to socio-demographics and attitudinal variables. Furthermore, the magnitude of the reduction in biases is lower for socio-demographic and behavioral variables compared to attitudinal variables.
Added Value: Our findings suggest –while considering the estimate-specific nature of bias–, first, that biases vary across different types of variables and, second, that the effects of PSW are not homogeneous across these types. Accordingly, we recommend not to restrict evaluations of attrition in a panel survey to a limited set of (socio-demographic) variables, because this may result in an underestimation of the magnitude of biases and an overestimation of the ability of PSW to reduce biases in other (types of) variables.
Methods & Data: Our analysis draws on data from a seven-wave web-based split-panel survey conducted during the campaign to the 2013 German federal election. The panel is supplemented with cross-sectional surveys that are comparable in terms of sampling and questionnaire. We use these cross-sections to assess attrition biases in the corresponding waves of the panel survey. The propensity score weights are calculated using the predicted propensity of respondents to participate in consecutive panel waves. The estimation of the response propensities draws on the data from the first panel wave. We assess the effect of applying these weights on attrition bias in 48 attitudinal, 38 behavioral, and 27 socio-demographic variables.
Results: Our results show that PSW successfully reduced biases in 72 out of the 113 variables. However, looking at the three types of variables, we find the rate of success to be lowest for behavioral variables compared to socio-demographics and attitudinal variables. Furthermore, the magnitude of the reduction in biases is lower for socio-demographic and behavioral variables compared to attitudinal variables.
Added Value: Our findings suggest –while considering the estimate-specific nature of bias–, first, that biases vary across different types of variables and, second, that the effects of PSW are not homogeneous across these types. Accordingly, we recommend not to restrict evaluations of attrition in a panel survey to a limited set of (socio-demographic) variables, because this may result in an underestimation of the magnitude of biases and an overestimation of the ability of PSW to reduce biases in other (types of) variables.
Access/Direct link Conference Homepage (presentation)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Germany (361)
- Does the Use of Mobile Devices (Tablets and Smartphones) Affect Survey Quality and Choice Behaviour...; 2015; Glenk, K.; Liebe, U.; Oehlmann, M.
- Does Personalized Feedback Increase Respondent Motivation?; 2015; Kroh, M.; Kuhne, S.
- Direction of Response Format in Web and Paper & Pencil Surveys; 2015
- Nonresponse and Measurement Bias in Web surveys ; 2015; Metzler, A.; Fuchs, M.
- Deep impact or no impact, evaluating opportunities for a new question type: Statement allocation on...; 2015; Schmidt, S.
- Approaches for Evaluating Online Survey Response Quality; 2015; Gluck, N.
- Positioning of Clarification Features in Open Frequency and Open Narrative Questions; 2015; Fuchs, M.; Metzler, A.
- A Systematic Generation of an Email Pool for Web Surveys; 2015; Silber, H.; Leibold, J.; Lischewski, J.; Schlosser, S.
- 640 Current trends in management of high-risk prostate cancer in Europe: Results of a web-based survey...; 2014; Briganti, A., Isbarn, H., Ost, P., Ploussard, G., Sooriakumaran, P., Van Den Bergh, R.C.N., Van Oort...
- Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis; 2014; Gnambs, T., Kaspar, K.
- Open-ended questions in Web Surveys-Using visual and adaptive questionnaire design to improve narrative...; 2014; Emde, M.
- Query on Data Collection for Social Surveys; 2014; Blanke, K., Luiten, A.
- Why Do Respondents Break Off Web Surveys and Does It Matter? Results From Four Follow-up Surveys; 2014; Rossmann, J., Blumenstiel, J. E., Steinbrecher, M.
- The Effectiveness of Mailed Invitations for Web Surveys and the Representativeness of Mixed-Mode versus...; 2014; Bandilla, W., Couper, M. P., Kaczmirek, L.
- Post-endodontic treatment of incisors and premolars among dental practitioners in Saarland: an interactive...; 2014; Mitov, G., Doerr, M., Nothdurft, F. P., Draenert, F., Pospiech, P. R.
- Mixed-Mode Designs bei Erhebungen mit sensitiven Fragen: Einfluss auf das Teilnahme- und Antwortverhalten...; 2014; Krug, G., Kriwy, P., Carstensen, J.
- Mining “Big Data” using Big Data Services ; 2014; Reips, U.-D., Matzat, U.
- Instant Interactive Feedback in Grid Questions: Reminding Web Survey; 2014; Kunz, T., Fuchs, M.
- What Does the Satisfaction with Democracy Measure Mean to Respondents in Different Countries? How Cross...; 2014; Behr, D., Braun, M.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- The Influence of the Answer Box Size on Item Nonresponse to Open-Ended Questions in a Web Survey; 2014; Zuell, C., Menold, N., Koerber, S.
- Does the Choice of Header Images influence Responses? Findings from a Web Survey on Students’...; 2014; Barth, A.
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- 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.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- 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.
- 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.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey; 2014; Sakshaug, J. W., Kreuter, F.
- GESIS Panel: Sample and Recruitment; 2014
- 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.
- 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.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Respondent Choice of Survey Mode; 2013; Fuchs, M.
- Development and validation of a single- item scale for the relative assessment of physical attractiveness...; 2013; Lutz, J.; Kemper, C. J.; Beierlein, C.; etc.
- Accounting for the Effects of Data Collection Method Application to the International Tobacco Control...; 2013; Thompson, M. E.; Huang, Y. C.; Boudreau, C.; Fong, G. T.; van den Putte, B.; Nagelhout, G. E.; Willemsen...
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- The Digital Divide in Europe; 2013; Zillien, N.; Marr, M.
- The Recruitment of the Access Panel of German Official Statistics from a Large Survey in 2006: Empirical...; 2013; Amarov, B.; Rendtel, U.
- Online, face-to-face and telephone surveys—Comparing different sampling methods in wine consumer...; 2013; Szolnoki, G., Hoffmann, D.
- Where does the Fair Trade price premium go? Confronting consumers' request with reality; 2013; Langen, N., Adenaeuer, L.