Web Survey Bibliography
The share of households without a landline phone, but aving at least one cell phone, is steadily growing, and so is evidence of corresponding non-coverage bias in landline surveys. Consequently, surveys increasingly use dual frame sampling, typically with a landline share of 60-80%. The aim of this paper is to find the optimal value of this share (i.e. mixture parameter), while considering survey error and costs.
For this purpose, the target population is divided into five strata, according to possession and availability of landlines and cell phones. Next, by optimizing the product of costs and the mean squared error across strata, we get the analytical solution (a 4th order polynomial). Finally, this approach is illustrated in eight countries with a 2008 Flash Eurobarometer dual frame survey. The questions cover various socioeconomic and political issues: the support of the EU and its currency; attitudes toward economic reforms; and evaluations of household income fluctuations. The optimal mixture parameter is estimated for different variables, countries, sources of population data, and cost options. The solution depends on the landline-cell phone cost ratio. However, it generally lies in a relatively flat optimal area, from 30-70%. Surprisingly, the results are almost invariant to variables, while linear regression (using strata weights and cost ratio) gives excellent prediction of the analytical solution. In countries where the share of the cell-only segment is not very high (less than 25%), it is optimal to have more landline units, and vice versa: where the cell-only segment is larger a predominately cell sample is optimal. However, this connection can be affected by changes in cost ratio, which is the most important factor in determining the optimal design allocation. When the cost of cell interviews is very high in relation to landline phone interviews, taking more landline units is optimal in all countries.
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Web survey bibliography - Mobile phone surveys (305)
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Device and Internet Use among Spanish-dominant Hispanics: Implications for Web Survey Design and Testing...; 2017; Trejo, Y. A. G.; Schoua-Glusberg, A.
- How to Design a Web Survey Using Spring Boot With MYSQL: a Romanien Network Case Study; 2017; Bucea-Manea-Tonis, Ro.; Bucea-Manea-Tonis, Ra.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- Mobile-only web survey respondents; 2016; Lugtig, P. J.; Toepoel, V.; Amin, A.
- Development and Pilot Test of a Mobile Application for Field Data Collection; 2016; Chiappetta, L.; Kerr, M. M.
- Are Initial Respondents Different from the Nonresponse Follow-Up Cases? A Study of Probability-Based...; 2016; Zeng, W.; Dennis, J. M.
- A Feasibility Study of Recruiting and Maintaining a Web Panel of People with Disabilities; 2016; Chandler, J.
- Why Do Web Surveys Take Longer on Smartphones?; 2016; Couper, M. P.; J. J.Peterson, G. J.
- Web surveys for offline rural communities ; 2016; Gichohi, B. W.
- Pre-Survey Text Messages (SMS) Improve Participation Rate in an Australian Mobile Telephone Survey:...; 2016; Dal Grande, E.; Chittleborough, C. R.; Campostrini, S.; Dollard, M.; Taylor, A. W.
- Short and Sweet? Length and Informative Content of Open-Ended Responses Using SMS as a Research Mode; 2016; Walsh, E.; Brinker, J. K.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices...; 2016; Toepoel, V.; Lugtig, P. J.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- Who Are the Internet Users, Mobile Internet Users, and Mobile-Mostly Internet Users?: Demographic Differences...; 2015; Antoun, C.
- Mobile Research Methods: Opportunities and challenges of mobile research methodologies. ; 2015; Toninelli, D. (Ed.); Pinter, R.; de Pedraza, P.
- Web Surveys Optimized for Smartphones: Are there Differences Between Computer and Smartphone Users?; 2015; Andreadis, I.
- Usability of the ACS Internet Instrument on Mobile Devices; 2015; Horwitz, R.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Emerging Technologies: The Rise of Mobile Devices: From Smartphones to Smart Surveys; 2015; Buskirk, T. D.
- PayPal? An Incentive to Check-out?; 2015; Franklin, J.; Rasmussen, C.; Pruitt, J.; Waller, D.
- Designing Bonsai Surveys: The small but perfectly formed survey experience to meet the needs of the...; 2015; Puleston, J.
- Open narrative questions in PC and smartphones: is the device playing a role?; 2015; Revilla, M.; Ochoa, C.
- Recruiting Respondents for a Mobile Phone Panel: The Impact of Recruitment Question Wording on Cooperation...; 2015; Busse, B.; Fuchs, M.
- Internet Research in Psychology; 2015; Gosling, S. D., Mason, W.
- Are Tailored Outreach Efforts Too Costly? An Assessment of a Responsive Design Approach to Control Costs...; 2015; Epps, S. R.; Getman, D. P.; Hall, L. M.; Hunter, J. A.
- Evaluating Visual Design Elements for Data Collection and Panelist Engagement; 2015; Christian, L. M.; Harm, D.; Langer Tesfaye, C.; Wells, T.
- Does the use of mobile devices (tablets and smartphones) affect survey quality and choice behaviour...; 2015; Liebe, U., Glenk, K., Oehlmann, M., Meyerhoff, J.
- When it comes to mobile respondent experience and data quality, survey design matters; 2014; Mitchell, N.
- The Changing Landscape of Technology and its Effect on Online Survey Data Collection; 2014; Mitchell, N.
- The need of and the demand for completing surveys on mobile devices; 2014; Toninelli, D., Revilla, M., Ochoa, C.
- Survey participation via mobile devices in a probability-based online-panel: Prevalence, determinants...; 2014; Poggio, T., Bosnjak, M., Weyandt, K.
- Keeping Surveys Valid, Reliable, and Useful: A Tutorial; 2014; Greenberg, M. R., Weiner, M. D.
- Improving Response Rates and Questionnaire Design for Mobile Web Surveys; 2014; de Bruijne, M., Wijnant, A.
- Does Survey Mode Still Matter? Findings from a 2010 Multi-Mode Comparison; 2014; Ansolabehere, S., Schaffner, B. F.
- Nonresponse and Mode Effects in Self- and Interviewer-Administered Surveys; 2014; Atkeson, L. R.; Adams, A. N.; Alvarez, M. R.
- Do Web surveys facilitate reporting less favourable opinions about law enforcement?; 2014; Boivin, R., Cordeau, G.
- Question Grouping and Matrices in Web Surveys: Using Response and Auxiliary Data to Examine Question...; 2014; Bilgen, I., Stern, M. J.
- The Grouping of Items in Mobile Web Surveys; 2014; Mavletova, A. M., Couper, M. P.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- 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.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.
- Comparison of Three Modes for a Crime Victimization Survey; 2013; Laaksonen, S., Heiskanen, M.
- Understanding Society Innovation Panel Wave 5: results from methodological experiments; 2013; Auspurg, K., Burton, J., Cullinane, C., Delavande, A., Fumagalli, L., Iacovou, M., Jaeckle, A., Kaminska...
- A Comparison of Results from a Spanish and English Mail Survey: Effects of Instruction Placement on...; 2013; Wang, K., Sha, M.
- Intra-individual variation of extreme response style in mixed-mode panel studies; 2013; Aichholzer, J.