Web Survey Bibliography
AGS covers many topics, including student satisfaction for his/her university experience. Using the complete AGS data set, we calculate two satisfaction factors from a set of satisfaction questions. This is done using the factor analysis (via principal components) method. First factor may be interpreted as a “general satisfaction” index, the second is a contrast between software (teaching, exams, graduation organization) and hardware (classrooms, libraries, cafeterias) evaluation. Factors are not directly observable, but we treat them as they are, for simplicity’s sake. They are continous, approximately normal variables.
Is the non-response process MAR (“Missing at Random”)? To say this we regress the response indicators on all the administrative variables (including sex, age, number of years needed for graduating, graduation mark, high school final mark, faculty, type of course) and the two satisfaction factors. There is a weak evidence that the respondents and non-respondents have different distribution of factor scores.
If we have to take any inference on the non-respondents we must assume that they are related to respondents in some way. The way is often the assumption that they are related through the auxiliary information, that is through variables known for both respondent and non-respondents.
We bootstrap the population to evaluate the ability of the calibration correction to improve the estimators of non-response. We try first to use the quasi-randomization approach to estimate propensity, then use these weights as a basis for calibration. Several combination for calibration variables are used. Faculty is always included as they are main subdivisions of the University and estimates by faculty are routinely required.
The paper analyzes reweighting adjustments for non-response in surveys carrying out a bootstrap evaluation of non-response adjusted estimators. In our study we consider a population made of students from the Bergamo University graduating in a specific period of time.
This population has been surveyed twice (web mode in both cases), before and after graduation. The ante-graduation survey (from now on, AGS) is a compulsory survey, the post-graduation survey (PGS) is not compulsory, therefore there was 56% non-response rate. Administrative (archive) data available for all the students. We apply the non-response process of the PGS in the analysis of AGS data. In this way, we have a controlled situation in which all survey variables, for both respondents and non-respondents are known. We avoid artificial assumptions on the non-response process.
Web survey bibliography (4086)
- Use of Paradata to Manage a Field Data Collection; 2009; Groves, R. M., Axinn, W., Lepkowski, J. M., Kirgis, N., Mosher, W.
- A Systematic Approach to Debugging in the Blaise Environment: An Author's Perspective; 2009; Sparks, P.
- Paradata and Blaise: A Review of Recent Applications and Research; 2009; O’Reilly, J.
- Development of Survey and Case Management facilities for organisations with minimal survey infrastructure...; 2009; Wensing, F.
- Be mindful of cellphone interviews; 2009; Anonymous
- Growth of Mobile-Only Population in the US and its impact on optimal designs; 2009; Srinivasan, R.
- The 'Functionally Mobile-Only' The true extent of coverage problems with landline only samples; 2009; De Keulenaer, F.
- Preference for Mobile Interview Surveys? Interplay of costs, errors and biases; 2009; Vehovar, V., Slavec, A.
- Mode or Mensch?: Respondent sensitivity to mode changes in data collection methods; 2009; McCutcheon, A. L.
- Generation (of) RDD Improving call efficiency of mobile RDD samples; 2009; Husztik, P.
- Flash Eurobarometer Goes Mobile: A practical review; 2009; Hideg, G.
- Are Respondents Sharing their Mobile Phones? Preliminary results based on a mobile phone panel in Germany...; 2009; Fuchs, M.
- Mobilisation: A general overview; 2009; Manchin, R.
- NOM Print Monitor: gereed voor de toekomst!; 2009; Petric, I., Appel, M.
- Asking Factual Knowledge Questions: Reliability in Web-Based, Passive Sampling Surveys ; 2009; Elo, K.
- If You Provide It, Will They Read It? Response Time Effects in a Choice Experiment; 2009; Vista, A. B., Rosenberger, R. S., Collins, A. R.
- Pictures in Web Surveys; 2009; Toepoel, V., Couper, M. P.
- National readership surveys: Moving from probability face-to-face surveys to Internet panels; 2009; Vehovar, V., Slavec, A., Petric, I., Sargac, M.
- Why don’t all Businesses report on Web?; 2009; Haraldsen, G.
- An experiment on the effects of non-response reweighting on estimators' precision in a web survey; 2009; Fabrizi, E., Biffignandi, S., Toninelli, D.
- Dynamic feedback in open-ended questions: Experiments on the visual design language of Web surveys; 2009; Fuchs, M.
- Effects of monetary incentives on participation in a two-wave online survey; 2009; Bandilla, W., Haas, I.
- Response Order and Response Distributions: The Format of the Response Options in a Web Survey; 2009; Tourangeau, R., Conrad, F. G., Couper, M. P., Balter, O.
- Anticipated estimation from a panel Web survey: the case of the presence of tourists in the Province...; 2009; Scaffai, G., Pratesi, M.
- Statistical analysis of on-line courses; 2009; Baelter, O.
- Methodological approaches of Web 2.0; 2009; Neubarth, W.
- Is this e-mail relevant? An eyetracking experiment on how potential respondents read e-mail invitations...; 2009; Kaczmirek, L., Faaß, T., Galesic, M.
- File transfer with built-in editing features; 2009; Erikson, J.
- From paper to internet: Design challenges when mixing modes in longitudinal surveys; 2009; Stax, H.-P., Thomsen, P.
- The Use of Audit Trails in Business Web Surveys; 2009; Snijkers, G., Morren, M.
- Yes, VASs can! Increasing the accuracy of survey measurements with computerized visual analogue scales...; 2009; Funke, F., Reips, U.-D.
- Using Mail Contact to Sample and Encourage Submission of Questionnaire Answers Over the Internet; 2009; Dillman, D. A., Messer, B. L., Millar, M. M.
- Improving the Design of Complex Matrix Questions; 2009; Couper, M. P., Tourangeau, R., Conrad, F. G.
- Use of Web surveys in Official Statistics; 2009; Bethlehem, J.
- Relations between functionality and usability of Web survey software tools: An empirical evaluation; 2009; Berzelak, N., Lozar Manfreda, K.
- Turning Grid Questions into Sequences in Business Web Surveys; 2009; Haraldsen, G., Bergstrøm, Y.
- The Electronic Questionnaire Experience in Business Surveys: mode effects on quality and on response...; 2009; Biffignandi, S., Siesto, G., Zeli, A.
- Reducing Measurement Error in Web Surveys; 2009; Couper, M. P.
- Reducing Measurement Errors in Surveys; 2009; De Leeuw, E. D.
- Mode Effects and Other Potential Biases in Panel-based Internet Surveys: Final Report; 2009; Taylor, P. A., Nelson, N. M., Grandjean, B. D., Anatchkova, B., Aadland, D.
- Findings from consumer surveys on Internet Shopping: A comparison of pre and post study consumer research...; 2009; Anonymous
- Pros and Cons of Internet Surveys Compared to Traditional Survey Methods; 2009; Benjamin, G. D.
- Visual Design Effects on Respondents’ Behavior in Web-Surveys; 2009; Greinoecker, A.
- Using online panels to conduct Web-based research: What works and what doesn’t; 2009; Goeritz, A.
- Balancing the tension between internal and external validity in online intervention research; 2009; Parks-Sheiner, A.
- Ethical Issues in Internet Research ; 2009; McKee, H., Porter, J.
- Making informed technology choices for online research; 2009; Macer, T.
- Practical advice on Internet Research: From Surveys on Social Computing; 2009; Konstan, J. A.
- True Web experiments; 2009; Reips, U.-D.
- Comments on the Articles (3) - Three Key Takeaways from the Zero Bank Debate; 2009; W.Link, M. W.