Web Survey Bibliography
Item nonresponse in self-administered modes such as Web and mail can be a major problem affecting survey data quality and, in some cases, may be as severe as unit nonresponse. Moreover, little is known about the determinants of item nonresponse in Web and mail household surveys. In this paper, we assess item nonresponse differences by Web and mail modes, question types (e.g. factual, attitudinal, behavioral) and formats (e.g. nominal, ordinal, multi-item, open-end, etc.), and respondent demographics (e.g. gender, age, education, race, and income) in three general public household surveys. For the three surveys, each conducted in the northwestern U.S. in 2007, 2008, and 2009, respectively, we used address-based sampling with the U.S. Postal Service‟s Delivery Sequence File and employed postal mail methods to send all contacts. Sampled respondents in each survey were presented with a) a mail-only response option, b) a mail response option with a Web follow-up sent two weeks later (i.e. mail+web), or c) a Web response option with a mail follow-up sent two weeks later (i.e. web+mail). The Web and mail questionnaires in each survey were designed very similarly in order to minimize and control for effects from visual design and layout. This paper serves to quantify and describe item nonresponse differences and the sources of those differences, and to identify potential ways of reducing item nonresponse in Web and mail modes of data collection.
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Web Survey Bibliography - USA (2171)
- The General Survey System Initiative at RTI International: An Integrated System for the Collection and...; 2013; Thalji, L., Mitchell, S., Hill, C. A., Suresh, R., Speizer, H., Pratt, D.
- Consolidation and Standardization of Survey Operations at a Decentralized Federal Statistical Agency; 2013; Nealon, J., Gleaton, E.
- Examination of the equivalence of self-report survey-based paper-and-pencil and internet data collection...; 2013; Weigold, A., Weigold, I. K., Russell, E. J.
- An Assessment of Incentive Versus Survey Length Trade-offs in a Web Survey of Radiologists; 2013; Ziegenfuss, J. Y., Niederhauser, B. D., Kallmes, D., Beebe, T. J.
- Clarifying Categorical Concepts in a Web Survey.; 2013; Redline, C. D.
- Using Online and Paper Surveys - The Effectiveness of Mixed-Mode Methodology for Populations Over 50; 2013; De Bernardo, D. H., Curtis, A.
- The Design of Grids in Web Surveys; 2013; Couper, M. P., Tourangeau, R., Conrad, F. G., Zhang, C.
- Survey Research; 2013; Abbott, M. L., McKinney, J.
- Understanding and Applying Research Design; 2013; Abbott, M. L., McKinney, J.
- The Science of Web Surveys; 2013; Tourangeau, R., Conrad, F. G., Couper, M. P.
- Virtual Research Methods; 2013; Hine, C.
- Informed Consent for Web Paradata Use; 2013; Couper, M. P., Singer, E.
- The Use of Mixed Methods in Organizational Communication Research; 2013; Salem, P. J.
- The Use of E-Questionnaires in Organizational Surveys; 2013; Brender-Ilan, Y., Vinitzky, G.
- Online Instruments, Data Collection, and Electronic Measurements: Organizational Advancements; 2013; Bocarnea, M. C., Reynolds, R. A., Baker, J. D.
- Convenient yet not a convenience sample: Jury pools as experimental subject pools; 2013; Murray, G. R., Rugeley, C. R., Mitchell, D.-G., Mondak, J. J.
- The equivalence of Internet versus paper-based surveys in IT/IS adoption research in collectivistic...; 2013; Fang, J., Wen, C., Prybutok, V.
- Examining the Gender Effects of Different Incentive Amounts in a Web Survey; 2013; Boulianne, S. J.
- Online Survey Software; 2013; Baker, J. D.
- Mode Effects in Free-list Elicitation: Comparing Oral, Written, and Web-based Data Collection; 2013; Gravlee, C. C., Bernard, H. R., R., Jacobsohn, A., R.Maxwell, C. R.
- Incentives for college student participation in web-based substance use surveys; 2013; Patrick, M. E., Singer, E., Boyd, C. J., Cranford, J. A., McCabe, S. E.
- The effect of short formative diagnostic web quizzes with minimal feedback; 2013; Baelter, O., Enstroem, E., Klingenberg, B.
- Increasing Web Survey Response Rates in Innovation Research: An Experimental Study of Static and Dynamic...; 2013; Sauermann, H.; Roach, M.
- Survey of Cloud Computing; 2013; Furht, B.
- Up Means Good: The Impact of Screen Position on Evaluative Ratings in Web Surveys.; 2013; Tourangeau, R., Conrad, F. G., Couper, M. P.
- WebSM Study: Speed and efficiency of online survey tools; 2012; Cehovin, G.; Vehovar, V.
- Worldwide online research spending; 2012
- What we can learn from unintentional mobile respondents; 2012; Peterson, G.
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- Using multivariate statistics, 6th Edition; 2012; Tabachnick, B. G., Fidell, L. S.
- Unintentional mobile respondents; 2012; Peterson, G.
- The smartphone psychology manifesto; 2012; Miller, G.
- The rise of the "connected viewer"; 2012; Smith, A., Boyles, J. L.
- The practice of social research; 2012; Babbie, E. R.
- The integration of facebook into class management: an exploratory study; 2012; Chou, P. N.
- The effects of item saliency and question design on measurement error in a self-administered survey; 2012; Stern, M. J., Smyth, J. D., Mendez, J.
- The cross platform report. Q2 -2012 - US; 2012
- Speed (necessarily) doesn’t kill: A new way to detect survey satisficing; 2012; Garland, P. et al.
- Smartphone ownership update: September 2012; 2012; Rainie, L.
- Research company spotlight - Mobile surveys; 2012
- Participation of mobile users in traditional online studies; 2012; Jue, A.
- Online survey statistics for the mobile future. Updated with Q3 2012 data; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- More dirty little secrets of online panel research.; 2012
- Mobile usability; 2012; Nielsen, J., Budiu, R.
- Mobile email opens report 2nd half 2011; 2012
- Media tracker; 2012
- Measuring the quality of governmental websites in a controlled versus an online setting with the ‘...; 2012; Elling, S. et al.
- Measuring modern media consumption; 2012; Arini, N.
- Guide to social science data preparation. Best practice throughout the data life cycle; 2012

