Web Survey Bibliography
Objective To evaluate non-response rates to follow-up online surveys using a prospective cohort of parents raising at least one child with an autism spectrum disorder. A secondary objective was to investigate predictors of non-response over time.
Materials and Methods Data were collected from a US-based online research database, the Interactive Autism Network (IAN). A total of 19 497 youths, aged 1.9–19 years (mean 9 years, SD 3.94), were included in the present study. Response to three follow-up surveys, solicited from parents after baseline enrollment, served as the outcome measures. Multivariate binary logistic regression models were then used to examine predictors of non-response.
Results 31 216 survey instances were examined, of which 8772 or 28.1% were partly or completely responded to. Results from the multivariate model found non-response of baseline surveys (OR 28.0), years since enrollment in the online protocol (OR 2.06), and numerous sociodemographic characteristics were associated with non-response to follow-up surveys (all p<0.05).
Discussion Consistent with the current literature, response rates to online surveys were somewhat low. While many demographic characteristics were associated with non-response, time since registration and participation at baseline played the greatest role in predicting follow-up survey non-response.
Conclusion An important hazard to the generalizability of findings from research is non-response bias; however, little is known about this problem in longitudinal internet-mediated research (IMR). This study sheds new light on important predictors of longitudinal response rates that should be considered before launching a prospective IMR study.
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Web Survey Bibliography (2070)
- Measurement error calibration in mixed-mode sample surveys; 2013; Buelens, B., van der Brakel, J.
- Optimal Resource Allocation in Adaptive Survey Designs; 2013; Calinescu, M.
- MOTUS: Modular online Time-Use Survey; 2013; Joeri, M., Ignace, G., van Tienoven, T. P., Djiwo, W.
- Response Burden in Official Business Surveys: Measurement and Reduction Practices of National Statistical...; 2013; Giesen, D., Bavdaz, M., Loefgren, T., Raymond-Blaess, V.
- Should the third reminder be sent? The role of survey response timing on web survey results; 2013; Rao, K., Pennington, J.
- Factors affecting the decision to participate in the internet option for the 2010 Census of Korea ; 2013; Lee, E., Kim, S.
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson , J.
- A standard with quality indicators for web panel surveys: a Swedish example; 2013; Nyfjaell, M.
- Web Panels for Official Statistics? ; 2013; Bethlehem, J., Cobben, F.
- Assessing Nonresponse Bias in the Green Technologies and Practices Survey; 2013; Meekins, B., Sverchkov, M., Stang, S.
- Using an Item Response Theory Approach to Measure Survey Mode of Administration Effects: Analysis of...; 2013; Mariano, L. T., Elliott, M. N.
- The Role of Mode Preference Questions in Predicting Mode-Specific Response Propensities; 2013; Lynn, P., Kaminska, O.
- Model-Based Mode of Data Collection Switching from Internet to Mail in the American Community Survey; 2013; Chesnut, J.
- Estimating Mode Effects Without Bias: A Randomized Experiment to Compare Mode Effects Between Face-to...; 2013; Rivers, D., Vavreck, L.
- Lotteries and study results in market research online panels; 2013; Goeritz, A.; Luthe, S. C.
- Respondent Rewards: Money for Nothing?; 2013; Martin, P.
- Did I Do That? How Trap Questions Can Hurt Data Quality; 2013; Phillips, K.
- Web Panel Representativeness; 2013; Bianchi, A., Biffignandi, S.
- Can creative web survey questionnaire design improve the response quality?; 2013; Angelovska, J., Mavrikiou, P. M.
- Use of mobile devices to answer online surveys: implications for research; 2013; Cunningham, J. A., Neighbors, C., Bertholet, N., Hendershot, C. S.
- Enhancing student engagement in student experience surveys: a mixed methods study; 2013; Webber, M., Lynch, S., Oluku, J.
- Where Am I? A Meta-Analysis of Experiments on the Effects of Progress Indicators for Web Surveys; 2013; Villar, A., Callegaro, M., Yang, Y.
- Field Lessons From the Delivery of Questionnaires to Young Adults Using Mobile Phones; 2013; van Heerden, A. C., Norris, S. A., Tollman, S. M., Stein, A. D., Richter, L. M.
- Attitudes of Nebraska Residents on Nebraska Water Management; 2013; Dillman, D. A., Edwards, M. L.
- On the Impact of Response Patterns on Survey Estimates from Access Panels; 2013; Enderle, T., Muennich, R., Bruch, C.
- Reconceptualizing Survey Representativeness for Evaluating and Using Nonprobability Samples; 2013; Fan, D. P.
- Unit Nonresponse and Weighting Adjustments: A Critical Review; 2013; Brick, J. M.
- Encouraging Record Use For Financial Asset Questions In A Web Survey; 2013; Couper, M. P., Ofstedal, M. B., Lee, S.
- Can Online Surveys Substitute Traditional Modes? An Error-Based Comparison of Online and On-Site Tourism...; 2013; Kim, N., Yu, X., Schwartz, Z.
- How incentives affect web-based survey response rates of athletic program donors; 2013; Alvarado, G., Callison, C.
- Investigating the Relationship among Prepaid Token Incentives, Response Rates, and Nonresponse Bias...; 2013; Parsons, N. L., Manierre, M. J.
- Web-Based Versus Traditional Paper Questionnaires: A Mixed-Mode Survey With a Nordic Perspective; 2013; Hohwue, L., Lyshol, H., Gissler, M., Hrafn Jonsson, S., Petzold, M., Obel, C.
- Going online with a face-to-face household panel: initial results from an experiment on the Understanding...; 2013; Jaeckle, A., Lynn, P., Burton, J.
- Targeted response inducement strategies on longitudinal surveys; 2013; Lynn, P.
- Measuring Up: Impact of mobile and segmentation on respondent behaviour; 2013; Luck, K.
- Survey Breakoffs in a Computer-Assisted Telephone Interview; 2013; McGonagle, K.
- Developing a New Mixed-Mode Methodology For a Provincial Park Camper Survey in British Columbia; 2013; Dyck, B. W.
- Exploring factors associated with respondent mode choice for surveys using mobile devices.; 2013; Walton, L.
- Responsive design for mixed-mode panel data; 2013; Bianchi, A., Biffignandi, S.
- Adjusting for bias in a mixed-mode CAWI survey on University students ; 2013; Clerici, R., Giraldo, A.
- Comparative analysis of data from web and face-to-face surveys. A case study on e-commerce in young...; 2013; Cappello, C., Pellegrino, D.
- Specific mixed-mode methodologies to include sensory disabled people in quantitative surveys; 2013; Sebastien, F., Marc, J., Patrick, I.
- Investigating the Bias of Alternative Statistical Inference Methods in Sequential Mixed-Mode Surveys; 2013; Suzer-Gurtekin, Z., Heeringa, S. G., Valliant, R. L.
- Random versus Systematic Error in a Mixed Mode Online-Telephone Survey; 2013; Hox, J., Scherpenzeel, A., Boeve, A., Boeve, A., de Leeuw, E. D.
- Online Survey Participation via Mobile Devices: implications for nonresponse; 2013; Poggio, T., Bosnjak, M.
- Mobile devices a way to recruit hard-to-reach groups? Results from a pilot study comparing desk top...; 2013; Toepoel, V., Lugtig, P. J.
- The Attention Span of a Goldfish: Impacts of Survey Mobilization on Respondents ; 2013; Luck, K.
- Web questionnaires in official population surveys: Do's and don'ts First experiments and impacts...; 2013; Blanke, K.
- Effects of Sponsorship on Response: Mixed-Mode Web and Mail Surveying ; 2013; Edwards, M. L., Dillman, D. A., Smyth, J.
- Does left still feel right? The optimal position of answer boxes in Web surveys - revisited; 2013; Lenzner, T., Kaczmirek, L.,Galesic, M.