Web Survey Bibliography
A core tenet of survey research is that the inferences one makes about the population can only be as good as the quality of the respondents in the sample. However, with declines in probability sample response rates and increases in non-probability Internet-based research, researchers have found it increasingly difficult to agree on the quality of a survey sample. Contributing to this difficulty is the variety of research studies that have evaluated the quality of survey data derived from probability-based and non-probability-based sources and the effectiveness of statistical methods to reduce error in data from
these sources. Specifically, some research has documented a greater average error among non-probability samples relative to probability samples (Chang & Krosnick, 2009; Yeager et al., in press), while other research has found few or small differences between the two. Other research has pointed to greater variability in results from surveys non-probability samples of Internet volunteers. For instance, Dedeker (2006) conducted the same study twice on the same Internet survey panel and reached two different business conclusions. An additional study found five to ten times greater variability in error among a sample of seven Internet surveys of non-probability samples versus seven probability sample surveys (Yeager et al., in press). Similarly-sized variability was found in the National Dutch Online Panel Comparison Study. Relatedly, statistical methods such as post-stratification survey weighting have inconsistent effects on non-probability sample surveys, and in some cases increase survey error. It is critically important to synthesize the survey accuracy studies summarized above as well as others. The present study will evaluate the evidence from more than 45 different studies have assessed the accuracy of non-probability sample surveys and the effectiveness of methods to improve their accuracy,
with the aim of helping researchers and consumers to have more informed expectations about data quality in their surveys.
Conference Homepage (abstract)
Web Survey Bibliography (6476)
- Using GIS to Target Address-Based Samples of Households for a Web (vs. Mail) Response: Evidence from...; 2013; Messer, B. L.
- Is Pushing the General Public to the Web in Address-Based Samples Cost Effective?; 2013; Lesser, V. M.
- Effects of Survey Sponsorship on Internet and Mail Response: Using Address- Based Sampling; 2013; Edwards, M. L.
- Grid Formats, Data Quality, and Mobile Device Use: A Questionnaire Design Approach; 2013; McClain, C., Crawford, S. D.
- Can Embedded Help Text Links in Web Survey Items Improve Data Quality?; 2013; Janson, N., Bennett, C., Caves, L., Cominole, M., Shepherd, B., Wine, J.
- Using the iPad as a Prize-Based Incentive to Boost Response Rates: A Case Study at Brigham Young University...; 2013; McClendon, R., Olsen, D.
- Can Google Consumer Surveys Help Pre-Test Alternative Versions of a Survey Question?: A Comparison of...; 2013; Stern, M. J., Welch, W. W.
- Online Panels: Recruitment Based on “Hot Topics” – What are the Consequences?; 2013; Andreasson, M., Martinsson, J.
- Social Network Analysis and Survey Response: How Facebook Data Can Supplement Survey Data; 2013; Sage, A.
- Surveywalls: A Breakthrough for Survey Customers or DIY Run Amok?; 2013; Wells, T., Dean, E., Rao, K., Murphy, J., Roe, D. J.
- Examining the Effects of Interventions to Obtain Participation via Less Expensive Modes: Results from...; 2013; Harris-Kojetin, L., Sengupta, M., Hobbs, M., Greene, A.
- Evaluating the Effect of a Non-Monetary Incentive in a Nationally Representative Mixed-Mode Establishment...; 2013; Sengupta, M., Harris-Kojetin, L., Hobbs, M., Greene, A.
- Dynamic Visual Design for List-Style Open-Ended Questions in Web Surveys; 2013; Fuchs, M.
- Classifying Mouse Movements to Predict Respondent Difficulty; 2013; Horwitz, R.
- Are You Seeing What I am Seeing? Exploring Response Option Visual Design Effects With Eye-Tracking; 2013; Libman, A., Smyth, J. D., Olson, K.
- Evaluating Interactive Feedback in Computer-Assisted Self-Interviewing (CASI); 2013; Hudson, M. L., Hupp, A., Zhang, C., Schroeder, H. M.
- Effective e-incentive for Online Study: Comparing Branded e-Gift Card and Virtual Cash Card; 2013; Jin, T., Duan, S., Lai, J. W., Link, M. W.
- First Contact Strategies for Web Surveys: Is a Phone Call or a Letter the More Effective Introduction...; 2013; Connelly, J., Sjoblom, M., Datta, R., Scholfield Hepburn, P.
- Response Format Effects in the Measurement of Employment; 2013; Rodkin, S., Thomas, R. K., Subias, S., Chu, C.
- Impact of Filter Questions on Estimates of Media Consumption; 2013; Cobb, C. L., Godinez, D., Thomas, R. K., Baim, J.
- The Effect of Survey Mode on Nonresponse Bias and Measurement Error: A Validation Approach; 2013; Kirchner, A., Felderer, B.
- Cross-Platform Measurement: User Experience With a Smartphone and Web Self- Reported Data Collection...; 2013; Petras, A. P., Duan, S., Dan, O.
- How Far Have We Come? The Lingering Digital Divide and Its Impact on the Representativeness of Internet...; 2013; Dennis, J. M., Cobb, C. L.
- How Do Different Sampling Techniques Perform in a Web-Only Survey? Results From a Comparison of a Random...; 2013; Bilgen, I., Stern, M. J., Wolter, K.
- Paradata in Web Surveys; 2013; Callegaro, M.
- Are Response Rates to a Web-Only Survey Spatially Clustered?; 2013; Fiorio, L., Stern, M. J., English, N., Bilgen, I., Curtis, B.
- The Effectiveness of Mailed Invitations for Web Surveys; 2013; Bandilla, W., Couper, M. P., Kaczmirek, L.
- Examining the Feasibility of SMS as a Contact Mode for a College Student Survey; 2013; Crawford, S. D., McClain, C., O'Brien, S., Nelson, T. F.
- The Impact on Web Survey Drop-Out Rates of Page Number Progress Indicators Used Throughout, Near the...; 2013; Walston, J. T., Cunningham, B., Medway, R.
- Survey Reminder Method Experiment: An Examination of Cost Efficiency and Reminder Mode Salience in the...; 2013; Anderson, M., Rogers, B., CyBulski, K., Hall, J. W., Alderks, C. E., Milazzo-Sayre, L.
- Using Qualitative and Quantitative Testing to Improve Hispanic Response Rates for Online Surveys; 2013; Pens, Y., Gentry, R. J.
- The Use of Email, Text Messages, and Facebook to Increase Response Rates Among Adolescents in a Longitudinal...; 2013; Fleeman, A., Francis, K., Henderson, T., Woodford, M., Jani, M.
- Use of Smart Phones/Text Messaging to Increase Response Rates; 2013; DuBray, P.
- Designing Surveys for Tablets and Smartphones; 2013; Lakhe, S., Nichols, E. M., Olmsted, M. G., King, T.
- Tablets as Data Entry Interfaces – Solving Data Cleaning and Transcription Issues During Data...; 2013; Costall, A.
- Effects of Response Format on Measurement of Readership; 2013; Thomas, R. K., Cobb, C. L., Baim, J.
- Potential Impact of Modifying the Fielding Time of a Web-Based Survey; 2013; Baum, H. M., Chandonnet, A.
- How Representative are Google Consumer Surveys?: Results From an Analysis of a Google Consumer Survey...; 2013; Krishnamurty, P., Tanenbaum, E., Stern, M. J.
- One Drink or Two: Does Quantity Depicted in an Image Affect Web Survey Responses?; 2013; Charoenruk, N., Stange, M.
- A Comparison Between Screen/Follow Item Format and Yes/No Item Format on a Multi-Mode Federal Survey; 2013; Hernandez,S. J., Arakelyan, S. N., Welch, V. E.
- Using Multiple Modes in Follow-Up Contacts in Random-Digit Dialing Surveys; 2013; Chowdhury, P. P.
- Tablets and Smartphones and Netbooks, Oh My! Effects of Device Type on Respondent Behavior; 2013; Ross, H., Mendelson, J., Lackey, M.
- Impacts of Unit Nonresponse in a Recontact Study of Youth; 2013; Mendelson, J., Viera Jr., L.
- Multi-Mode Survey Administration: Does Offering Multiple Modes at Once Depress Response Rates?; 2013; Newsome, J., Levin, K., Langetieg, P., Vigil, M., Sebastiani, M.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- Utilizing the Web in a Multi-Mode Survey; 2013; Venkataraman, L.
- Changing to a Mixed-Mode Design: The Role of Mode in Respondents’ Decisions About Participation...; 2013; Collins, D., Mitchell, M., Toomes, M.
- Comparing the Effects of Mode Design on Response Rate, Representativeness, and Cost Per Complete in...; 2013; Tully, R.
- Internet Response for the Decennial Census – 2012 National Census Test; 2013; Reiser, C.
- The Effects of Pushing Web in a Mixed-Mode Establishment Data Collection; 2013; Ellis, C.