Web Survey Bibliography
When will a nonprobability sample look like a probability sample? This key question in survey research has reemerged with the proliferation of new, nonprobability methods for collecting social science data (Baker et al., 2013). Among these, Internet surveys offer myriad advantages in data collection, including reduced costs, faster survey administration, and possibly more accurate self-reports (Chang & Krosnick, 2010; Fricker & Schonlau, 2002; Greenlaw & Brown-Welty, 2009; Wright, 2005) as compared with other survey methods. These surveys also open new research possibilities, allowing for the presentation of experimental stimuli to broad national samples (Couper, 2000; Iyengar, 2011; Skitka & Sargis, 2006). But many of these advantages can only be reaped if data collected from nonprobability samples can be transformed to reflect the public. Inasmuch as this is not the case, there is reason for concern. The majority of Internet surveys use opt-in, nonprobability samples, for which generalizability is not assured (Baker et al., 2010; Couper, 2000).
As nonprobability data collection methods continue to propagate, it becomes increasingly important to demarcate conditions under which data from samples with broad but incomplete coverage and potentially problematic sampling frames will produce results similar to those of probability samples. The ability to account for any differences will likely depend on two critical factors: the type of inference we hope to make and the model we use to translate between the data collected and society as a whole. …
Web survey bibliography - International Journal of Public Opinion Research (21)
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- When will Nonprobability Surveys Mirror Probability Surveys? Considering Types of Inference and Weighting...; 2016; Pasek, J.
- Reducing Underreports of Behaviors in Retrospective Surveys: The Effects of Three Different Strategies...; 2016; Lugtig, P. J.; Glasner, T.; Boeve, 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.
- Measuring Political Participation—Testing Social Desirability Bias in a Web-Survey Experiment; 2014; Persson, M., Solevid, M.
- Is it what you say, or how you say It? An experimental analysis of the effects of invitation wording...; 2014; Fazekas, Z., Wall, M. T., Krouwel, A.
- A Comparison of the Quality of Questions in a Face-to-face and a Web Survey; 2013; Revilla, M., Saris, W. E.
- Evaluation of an online (opt-in) panel for public participation geographic information systems surveys...; 2012; Brown, G., Weber, D., Zanon, D., de Bie, K.
- Assessing Cross-National Equivalence of Measures of Xenophobia: Evidence from Probing in Web Surveys; 2012; Behr, D., Braun, M., Kaczmirek, L.
- Efficiency of Different Recruitment Strategies for Web Panels; 2012; Hansen, K. M., Pedersen, R. T.
- Do Questions about Watching Internet Pornography Make People Watch Internet Pornography? A Comparison...; 2012; Peter, J., Valkenburg, P. M.
- Refining the Total Survey Error Perspective; 2011; Smith, T. W.
- Seeing Through the Eyes of the Respondent: An Eye-tracking Study on Survey Question Comprehension; 2011; Lenzner, A., Kaczmirek, L., Galesic, M.
- Should I Stay or Should I go: The Effects of Progress Feedback, Promised Task Duration, and Length of...; 2011; Yan, T., Conrad, F. G., Tourangeau, R., Couper, M. P.
- The Effect of Phrasing Scale Items in Low-Brow or High-Brow Language on Responses; 2009; Blasius, J., Friedrichs, J.
- Mode Differences Between Face-to-Face and Web Surveys: An Experimental Investigation of Data Quality...; 2009; Heerwegh, D.
- Cognitive Aspects of Survey Measurement and Mismeasurement; 2003; Tourangeau, R.
- Item Nonresponse: Distinguishing between don't Know and Refuse; 2002; Pamela J. Shoemaker, Martin Eichholz and Elizabeth A. Skewes
- New approaches to assessing opinion: The prospects for electronic mail surveys; 2002; Best, S. J., Krueger, B. S.
- Formal features of rating scales and their interpretation of question meaning; 1998; Schwarz, N., Grayson, C. E., Knauper, B.
- The numeric values of rating scales: A comparison of their impact in mail surveys and telephone interviews...; 1994; Schwarz, N., Hippler, H. J.