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 - Internet Survey Methodology workshop 2009 (24)
- 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.
- Comparing the results of Web surveys on volunteer versus probabilistically selected panels of participants...; 2009; Galesic, 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.
- Interactive aspects of web surveys; 2009; 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.
- Donations to charity as incentives in online panels; 2009; Goeritz, A.; Hox, J.
- 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.