Web Survey Bibliography
Title Non-Observation Bias in an Address-Register-Based CATI/CAPI Mixed Mode Survey
Author Lipps, O.
Source methods, data, analyses, 10, 1, pp. 5-24
Year 2016
Access date 30.05.2016
Full text PDF (814 KB)
Abstract Landline surveys suffer from an increasing risk of excluding a relevant share of the population. To analyze and correct telephone coverage issues, face-to-face surveys are often used, which contain questions about landline ownership and registration. Others use dual frame approaches and compare results from the landline with another mode. However, such surveys lack information about unobserved sample members. In this article we analyze representation bias using a household survey with a sample drawn from a population register, where landline is used for households with a matched landline, and face-to-face for those without. We distinguish between the different components of nonobservation, including landline undercoverage, non-contact, and non-cooperation, by either incorporating face-to-face sample members or not, and by the fieldwork phases to recruit households and individuals. Our main interest is how biases from each of these components add up to a final representation bias in the responding sample. In addition, we analyze income and deprivation differences by either including face-to-face sample members or not. The strongest representation bias in the telephone sample on the household level is caused by telephone undercoverage. The combined sample suffers much less from representation bias, which mostly stems from noncooperation. In terms of income and deprivation differences, our results show that the face-to-face sample is poorer than the telephone sample and needs to be considered for unbiased estimates. Based on these findings we offer some fieldwork recommendations to help reduce selection bias based on the different reasons for nonobservation.
Access/Direct link Journal Homepage (abstract) / (full text)
Year of publication2016
Bibliographic typeJournal article
Web survey bibliography - 2016 (264)
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- Detecting careless respondents in web-based questionnaires: Which method to use?; 2016; Niesen, A. S. M.; Meijer, R. R.; Tendeiro, J. N.
- Web surveys for offline rural communities ; 2016; Gichohi, B. W.
- On-line life history calendar and sensitive topics: A pilot study; 2016; Morselli, D.; Berchtold, A.; Granell, J.-C. S.; Berchtold, And.
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- Problems and Prospects in Survey Research; 2016; Moy, P.; Murphy, J.
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- Forecasting proportional representation elections from non-representative expectation surveys; 2016; Graefe, A.
- Short and Sweet? Length and Informative Content of Open-Ended Responses Using SMS as a Research Mode; 2016; Walsh, E.; Brinker, J. K.
- Mixing modes of data collection in Swiss social surveys: Methodological report of the LIVES-FORS mixed...; 2016; Roberts, C.; Joye, D.; Staehli, M. E.
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- Options for Fielding and Analyzing Web Surveys; 2016; Schonlau, M.; Couper, M. P.
- Report of the Inquiry into the 2015 British general election opinion polls; 2016; Sturgis, P., Baker, N., Callegaro, M., Fisher, St., Green, J., Jennings, W., Kuha, J., Lauderdale, B...
- Sample Representation and Substantive Outcomes Using Web With and Without Incentives Compared to Telephone...; 2016; Lipps, O.; Pekari, N.
- Effects of Data Collection Mode and Response Entry Device on Survey Response Quality; 2016; Ha, L.; Zhang, Che.; Jiang, W.
- The Dynamic Identity Fusion Index: A New Continuous Measure of Identity Fusion for Web-Based Questionnaires...; 2016; Jimenez, J.; Gomez, A.; Buhrmester, M.; Whitehouse, H.; Swann, W. B.
- Navigation Buttons in Web-Based Surveys: Respondents’ Preferences Revisited in the Laboratory; 2016; Romano Bergstrom, J. C.; Erdman, C.; Lakhe, S.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- “Money Will Solve the Problem”: Testing the Effectiveness of Conditional Incentives for...; 2016; DeCamp, W.; Manierre, M. J.
- Effects of Incentive Amount and Type of Web Survey Response Rates; 2016; Coopersmith, J.; Vogel, L. K.; Bruursema, T.; Feeney, K.
- Effect of a Post-paid Incentive on Response to a Web-based Survey; 2016; Brown, J. A.; Serrato, C. A.; Hugh, M.; Kanter, M. H.; A.; Spritzer, K. L.; Hays, R. D.
- Dropouts in Longitudinal Surveys; 2016; Lugtig, P. J.; De Leeuw, E. D.
- Participant recruitment and data collection through Facebook: the role of personality factors; 2016; Rife, S. C.; Cate, K. L.; Kosinski, M.; Stillwell, D.
- Evaluating a New Proposal for Detecting Data Falsification in Surveys; 2016; Simmons, K.; Mercer, A. W.; Schwarzer, S.; Courtney, K.
- Quantifying Under- and Overreporting in Surveys Through a Dual-Questioning-Technique Design. ; 2016; de Jong , M.; Fox, J.-P.; Steenkamp, J. - B. E. M.
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- Solving the Nonresponse Problem With Sample Matching?; 2016
- Do Polls Still Work If People Don't Answer Their Phones?; 2016; Edwards-Levy, A.; Jackson, N. M.
- A Framework of Incorporating Thai Social Networking Data in Online Marketing Survey; 2016; Jiamthapthaksin, R.; Aung, T. H.; Ratanasawadwat, N.
- Development of a scale to measure skepticism toward electronic word-of-mouth; 2016; Zhang, Xia.; Ko, M.; Carpenter, D.
- Improving social media measurement in surveys: Avoiding acquiescence bias in Facebook research; 2016; Kuru, O.; Pasek, J.
- Psychological research in the internet age: The quality of web-based data; 2016; Ramsey, S. R.; Thompson, K. L.; McKenzie, M.; Rosenbaum, A.
- Internet Abusive Use Questionnaire: Psychometric properties; 2016; Calvo-Frances, F.
- The impact of academic sponsorship on Web survey dropout and item non-response; 2016; Allen, P. J.; Roberts, L. D.
- Measuring Generalized Trust: An Examination of Question Wording and the Number of Scale Points; 2016; Lundmark, S.; Giljam, M.; Dahlberg, S.