Web Survey Bibliography
A popular example for this is the ‘forced response‘ option, whose impact will be analysed within this research project. The ‘forced response’ option is commonly described as a possibility to force the respondent to give an answer to each question that is asked. In most of the online survey computer software, it is easily achieved by enabling a checkbox.
Relevance: There has been a tremendous increase in the use of this option, however, the inquirers are often not aware of the possible consequences. In software manuals, this option is praised as a strategy that significantly reduces item non-response. In contrast, research studies offer many doubts that counter this strategy (Kaczmirek 2005, Peytchev/Crawford 2005, Dillman/Smyth/Christian 2009, Schnell/Hill/Esser 2011, Jacob/Heinz/Décieux 2013). They are based on the assumption that respondents typically have plausible reasons for not answering a question (such as not understanding the question; absence of an appropriate category; personal reasons e.g. privacy). Research Question: Our thesis is that forcing the respondents to select an answer might cause two scenarios: Increasing unit non-response (increased dropout rates); Decreasing validity of the answers (lying or random answers). Methods and Data: To analyse the consequences of the implementation of ‘forced response’ option, we use split ballot field experiments. Our analysis focuses especially on dropout rates and response behaviour. Our first split ballot experiment was carried out in July 2014 (n=1056) and we have planned a second experiment for February 2015, so that we will be able to present our results based on strong data evidence. First results:If the respondents are forced to answer each question, they will - cancel the study earlier and- choose more often the response category “No” (in terms of sensitive issues).
Web survey bibliography (366)
- Grundzüge des Datenschutzrechts und aktuelle Datenschutzprobleme in der Markt- und Sozialforschung; 2017; Schweizer, A.
- Web- and Phone-based Data Collection using Planned Missing Designs; 2017; Revelle, W.; Condon, M. D.; Wilt, J.; French, A. J.; Brown, A.; Elleman, G. L.
- Finding and Investigating Geographical Data Online; 2017; Martin, D.; Cockings, S.; Leung, S.
- CAQDAS at a Crossroads: Affordances of Technology in an Online Environment; 2017; Silver, C.; Bulloch, L. S.
- Artificial Intelligence/Expert Systems and Online Research; 2017; Brent, E.
- Improving the Effectiveness of Online Data Collection by Mixing Survey Modes; 2017; Dillman, D. A.; Hao, F.; Millar, M. M.
- Online Survey Software; 2017; Kaczmirek, L.
- Online Survey Design; 2017; To, N.
- Sampling Methods for Online Surveys; 2017; Fricker, R. D.
- Research Design and Tools for Online Research; 2017; Hewson, C. M.
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Using Visual Analogue Scales in eHealth: Non-Response Effects in a Lifestyle Intervention; 2016; Kuhlmann, T.; Reips, U.-D.; Wienert, J.; Lippke, S.
- A Feasibility Study of Recruiting and Maintaining a Web Panel of People with Disabilities; 2016; Chandler, J.
- Inferences from Internet Panel Studies and Comparisons with Probability Samples; 2016; Lachan, R.; Boyle, J.; Harding, R.
- Exploring the Gig Economy Using a Web-Based Survey: Measuring the Online 'and' Offline Side...; 2016; Robles, B. J.; McGee, M.
- Facebook, Twitter, & Qr codes: An exploratory trial examining the feasibility of social media mechanisms...; 2016; Gu, L. L.; Skierkowski, D.; Florin, P.; Friend, K.; Ye, Y.
- Distractions: The Incidence and Consequences of Interruptions for Survey Respondents ; 2016; Ansolabehere, S.; Schaffner, B. F.
- Mixing modes of data collection in Swiss social surveys: Methodological report of the LIVES-FORS mixed...; 2016; Roberts, C.; Joye, D.; Staehli, M. E.
- Representative web-survey!; 2016; Linde, P.
- The Analysis of Respondent’s Behavior toward Edit Messages in a Web Survey; 2016; Park, Y.
- Refining the Web Response Option in the Multiple Mode Collection of the American Community Survey; 2016; Hughes, T.; Tancreto, J.
- The Utility of an Online Convenience Panel for Reaching Rare and Dispersed Populations; 2016; Sell, R.; Goldberg, S.; Conron, K.
- Comparing online and telephone survey results in the context of a skin cancer prevention campaign evaluation...; 2016; Hollier, L.P.; Pettigrew, S.; Slevin, T.; Strickland, M.; Minto, C.
- Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk; 2016; Berinsky, A.; Huber, G. A.; Lenz, G. S.
- Setting Up an Online Panel Representative of the General Population The German Internet Panel; 2016; Blom, A. G.; Gathmann, C.; Krieger, U.
- 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.
- Navigation Buttons in Web-Based Surveys: Respondents’ Preferences Revisited in the Laboratory; 2016; Romano Bergstrom, J. C.; Erdman, C.; Lakhe, S.
- Web-based versus Paper-based Survey Data: An Estimation of Road Users’ Value of Travel Time Savings...; 2016; Kato, H.; Sakashita, A.; Tsuchiya, Tak.
- Reminder Effect and Data Usability on Web Questionnaire Survey for University Students; 2016; Oishi, T.; Mori, M.; Takata, E.
- Reducing Underreports of Behaviors in Retrospective Surveys: The Effects of Three Different Strategies...; 2016; Lugtig, P. J.; Glasner, T.; Boeve, A.
- 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.
- What drives the participation in a monthly research web panel? The experience of ELIPSS, a French random...; 2016; Legleye, S; Cornilleau, A.; Razakamanana, N.
- Quantifying Under- and Overreporting in Surveys Through a Dual-Questioning-Technique Design. ; 2016; de Jong , M.; Fox, J.-P.; Steenkamp, J. - B. E. M.
- Take the money and run? Redemption of a gift card incentive in a clinician survey. ; 2016; Chen, J. S.; Sprague, B. L.; Klabunde, C. N.; Tosteson, A. N. A.; Bitton, A.; Onega, T.; MacLean, C....
- Electronic and paper based data collection methods in library and information science research: A comparative...; 2016; Tella, A.
- A Technical Guide to Effective and Accessible web Surveys; 2016; Baatard, G.
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Methods can matter: Where Web surveys produce different results than phone interviews; 2016; Keeter, S.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- Will They Stay or Will They Go? Personality Predictors of Dropout in Online Study; 2016; Nestler, S.; Thielsch, M.; Vasilev, E.; Back, 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.
- Revisiting “yes/no” versus “check all that apply”: Results from a mixed modes...; 2016; Nicolaas, G.; Campanelli, P.; Hope, S.; Jaeckle, A.; Lynn, P.
- A Statistical Approach to Provide Individualized Privacy for Surveys; 2016; Esponda, F.; Huerta, K.; Guerrero, V. M.
- Online and Social Media Data As an Imperfect Continuous Panel Survey; 2016; Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.