Web Survey Bibliography
A number of surveys, including many student surveys, rely on vague quantifiers to measure behaviors important in evaluation. The ability of vague quantifiers to provide valid information, particularly compared to other measures of behaviors, has been questioned both within both survey research generally and educational research specifically. Still, there is a dearth of research on whether vague quantifiers or numeric responses perform better in regards to validity. This study examines measurement properties of frequency estimation questions through the assessment of predictive validity, which has also been shown to be important in examining measurement properties of competing question formats. Data from the National Survey of Student Engagement (NSSE), a preeminent survey of university students, is analyzed, in which two psychometrically tested benchmark scales, active and collaborative learning and student-faculty interaction, are measured through both vague quantifier and numeric responses. Predictive validity is assessed through correlations and regression models relating both vague and numeric scales to grades in school and two education experience satisfaction measures. Results support the view that the predictive validity is higher for vague quantifier scales, and hence better measurement properties, compared to numeric responses. These results are discussed in light of other findings on measurement properties of vague quantifiers and numeric responses, suggesting that vague quantifiers may be a useful measurement tool for behavioral data, particularly when it is the relationship between variables that are of interest.
Web survey bibliography - Survey Research Methods (34)
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Can we assess representativeness of cross-national surveys using the education variable?; 2016; Ortmanns, V.; Schneider, S.
- Smartphones vs PCs: Does the Device Affect the Web Survey Experience and the Measurement Error for...; 2016; Toninelli, D.; Revilla, M.
- Are Final Comments in Web Survey Panels Associated with Next-Wave Attrition?; 2016; McLauchlan, C.; Schonlau, M.
- Sensitive Questions in Online Surveys: An Experimental Evaluation of Different Implementations of the...; 2016; Hoglinger, M.; Jann, B.; Diekmann, A.
- Helping respondents provide good answers in Web surveys; 2016; Couper, M. P.; Zhang, C.
- Stable Relationships, Stable Participation? The Effects of Partnership Dissolution and Changes in Relationship...; 2016; Mueller, B.; Castiglioni, L.
- Identifying Pertinent Variables for Nonresponse Follow-Up Surveys. Lessons Learned from 4 Cases in Switzerland...; 2016; Vandenplas, C.; Joye, D.; Staehli, M. E.; Pollien, A.
- Sunday shopping – The case of three surveys; 2016; Bethlehem, J.
- Revisiting “yes/no” versus “check all that apply”: Results from a mixed modes...; 2016; Nicolaas, G.; Campanelli, P.; Hope, S.; Jaeckle, A.; Lynn, P.
- Going Online with a Face-to-Face Household Panel: Effects of a Mixed Mode Design on Item and Unit Non...; 2015; Burton, J.; Jaeckle, A.; Lynn, P.
- Impact of mixed modes on measurement errors and estimates of change in panel data; 2015; Cernat, A.
- Is Vague Valid? The Comparative Predictive Validity of Vague Quantifiers and Numeric Response Options...; 2014; Al Baghal, T.
- The Effect of Answering in a Preferred Versus a Non-Preferred Survey Mode on Measurement; 2014; Smyth, J. D., Olson, K., Kasabian, A.
- Speeding in Web Surveys: The tendency to answer very fast and its association with straightlining; 2013; Conrad, F. G.; Zhang, Che.
- The Recruitment of the Access Panel of German Official Statistics from a Large Survey in 2006: Empirical...; 2013; Amarov, B.; Rendtel, U.
- Relative Mode Effects on Data Quality in Mixed-Mode Surveys by an Instrumental Variable; 2013; Vannieuwenhuyze, J. T. A., Revilla, M.
- Is the Sky Falling? New Technology, Changing Media, and the Future of Surveys; 2013; Couper, M. P.
- On the Impact of Response Patterns on Survey Estimates from Access Panels; 2013; Enderle, T., Muennich, R., Bruch, C.
- Survey Breakoffs in a Computer-Assisted Telephone Interview; 2013; McGonagle, K.
- Informed Consent for Web Paradata Use; 2013; Couper, M. P., Singer, E.
- Measurement invariance and quality of composite scores in a face-to-face and a web survey; 2013; Revilla, M.
- Assessing the Magnitude of Non-Consent Biases in Linked Survey and Administrative Data; 2012; Sakshaug, J. W., Kreuter, F.
- Quality in Unimode and Mixed-Mode designs: A Multitrait-Multimethod approach; 2010; Revilla, M.
- Elaborate Item Count Questioning: Why Do People Underreport in Item Count Responses?; 2010; Hirai, Y., Tsuchiya, Ta.
- The impact of incentives and interview methods on response quantity and quality in diary- and booklet...; 2010; Bonke, J., Fallesen, P.
- Does Visual Appeal Matter? Effects of Web Survey Aesthetics on Survey Quality; 2010; Mahon-Haft, T., Dillman, D. A.
- The Mobile-only Population in Portugal and Its Impact in a Dual Frame Telephone Survey; 2009; Vicente, P., Reis, E.
- Impact of mixed survey modes on physical activity and fruit/vegetable consumption: A longitudinal study...; 2009; Nigg, C. R., Motl, R. W., Wong, K. T., Yoda L. U., McCurdy, D. K., Paxton, R., Horwath, C. C., Dishman...
- Nonresponse in the Recruitment of an Internet Panel Based on Probability Sampling; 2009; Hoogendoorn, A., Daalmans, J.
- Differential response rates in postal and Web-based surveys in older respondents; 2009; Bech, M., Kristensen, M. B.
- An evaluation of the weighting procedures for an online access panel survey; 2008; Loosveldt, G., Sonck, N.
- Internet Surveys: Can Statistical Adjustments Eliminate Coverage Bias?; 2008; Dever, J. A., Rafferty, A., Valliant, R. L.
- Estimation of the effects of measurement characteristics on the quality of survey questions; 2007; Saris, W. E., Gallhofer, I.