Web Survey Bibliography
The present analysis has been made possible by the survey on graduates' condition that is carried out every year by the Inter
‐universities Consortium ALMALAUREA1. The survey makes it possible to analyse the most recent labour market trends through an examination of the career opportunities available for the Italian graduates of the universities taking part in the Consortium during the 5 years on from graduation. All graduates are contacted 1, 3 and 5 years on from graduation. More specifically, the data have been collected during the last survey conducted by ALMALAUREA in 2008 (over 287,000 graduates examined). This survey also involved all first and second level (=cycle of the Bologna Process) graduates from the class of 2007 (about 140,000). The huge number of graduates involved has determined the necessity to use survey methods that allow the reduction of costs and duration. This objective has been achieved through the introduction of two survey methods: CAWI and CATI. More precisely, the graduates having a mailbox (85% of the cohort) have been emailed and asked to answer to a questionnaire on the web site of ALMALAUREA. The survey procedure also included two e‐mail reminders. Afterwards, all graduates who had not answered to the online questionnaire have been contacted by phone. ‐to‐entry into the labour market and so on. These pieces of information are integrated by the huge quantity of data on the sociodemographic characteristics of graduates (e.g. social origins, gender, age), pre‐university studies, academic studies (e.g. degree course, graduation mark) and further experiences made during studies (foreign languages and IT skills, internships, study experiences made abroad and work experiences). It is possible that the survey methods used may have influenced the answer given by graduates. In other words, since the information have been collected through different survey tools (CAWI and CATI), they may have caused distortions that are not casual. For example, the presence/absence of interviewers is an important determinant for the quality of the information collected. On the other hand, because of the cultural level of the cohort involved in the interview, the contribution given by the interviewer may be limited; in some cases it may even be counterproductive, since they may influence the answer of the graduates. In consideration of the complexity of the subject that is dealt with, it has become important to determine if there are significant differences between the answers given by those who filled in the online questionnaire and those who gave their answers during the telephone interview. This need has also been confirmed by the fact that these two groups of graduates have also turned out during some preliminary analysis to be different in terms of their studies and area of residence. The method for evaluating an error deriving from a differentiated treatment (CATI or CAWI) will be developed by following a particular approach that is referred to the typical notions of the so‐called “causal inference”. This problem may be faced by referring to the approach proposed by Rosembaum and Rubin (1983), that is known as propensity score. The authors demonstrate that, having in hand several information which characterise the individuals and which are related to the time that preceded the treatment, it is possible to create groups of individuals having similar characteristics. These groups are, therefore, theoretically deconditioned by the kind of undergone treatment. Within this groups of individuals it is possible to compare the target variable (e.g. the occupational status) among those who have undergone the treatment and those who have not or just have undergone a different treatment. ALMALAUREA has also implemented a monitoring system of selection bias due to different data collection techniques. In this system an innovative approach was used (Camillo and D’Attoma, 2008). It involves a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The aim of ALMALAUREA is to measure and eventually to evaluate the effect of the undergone treatment on the answers given by graduates.
The survey enabled us to collect the main information related to academic and work experiences made after graduation: employment condition at the time of the interview, characteristics of the job (contract, branch of activity, earning), time
Conference homepage (abstract)
Web survey bibliography (388)
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- Push2web or less is more? Experimental evidence from a mixed-mode population survey at the community...; 2017; Neumann, R.; Haeder, M.; Brust, O.; Dittrich, E.; von Hermanni, H.
- Rates, Delays, and Completeness of General Practitioners’ Responses to a Postal Versus Web-Based...; 2017; Sebo, P.; Maisonneuve, H.; Cerutti, B.; Pascal Fournier, J.; Haller, D. M.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.
- Improving survey response rates: The effect of embedded questions in web survey email Invitations; 2017; Liu, M.; Inchausti, N.
- Enhancing survey participation: Facebook advertisements for recruitment in educational research; 2017; Forgasz, H.; Tan, H.; Leder, G.; McLeod, A.
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- “Better do not touch” and other superstitions concerning melanoma: the cross-sectional web...; 2016; Gajda, M.; Kamińska-Winciorek, G.; Wydmański, J.; Tukiendorf, A.
- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Population Survey Features and Response Rates: A Randomized Experiment; 2016; Guo, Y.; Kopec, J.; Cibere, J.; Li, L. C.; Goldsmith, C. H.
- The Effects of a Delayed Incentive on Response Rates, Response Mode, Data Quality, and Sample Bias in...; 2016; McGonagle, K., Freedman, V. A.
- Can Student Populations in Developing Countries Be Reached by Online Surveys? The Case of the National...; 2016; Langer, A., Meuleman, B., Oshodi, A.-G. T., Schroyens, M.
- How to maximize survey response rates ; 2016; DeVall, R.; Colby, C.
- Impact of Field Period Length and Contact Attempts on Representativeness for Web Survey ; 2016; Bertoni, N.; Turakhia, C.; Magaw, R.; Ackermann, A.
- Have You Taken Your Survey Yet? Optimum Interval for Reminders in Web Panel Surveys ; 2016; Kanitkar, K. N.; Liu, D.
- User Experience and Eye-tracking: Results to Optimize Completion of a Web Survey and Website Design ; 2016; Walton, L.; Ricci, K.; Libman Barry, A.; Eiginger, C.; Christian, L. M.
- A Multi-phase Exploration Into Web-based Panel Respondents: Assessing Differences in Recruitment, Respondents...; 2016; Redlawsk, D.; Rogers, K.; Borie-Holtz, D.
- Exploring the Feasibility of Using Facebook for Surveying Special Interest Populations ; 2016; Lee, C.; Jang, S.
- National Estimates of Sexual Minority Women Alcohol Use through Web Based Respondent Driven Sampling...; 2016; Farrell Middleton, D.; Iachan, R.; Freedner-Maguire, N.; Trocki, K.; Evans, C.
- User Experience Considerations for Contextual Product Surveys on Smartphones ; 2016; Sedley, A.; Mueller, H.
- Web Probing for Question Evaluation: The Effects of Probe Placement ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Berrigan, D.
- Early-bird Incentives: Results From an Experiment to Determine Response Rate and Cost Effects ; 2016; De Santis, J.; Callahan, R.; Marsh, S.; Perez-Johnson, I.
- Effects of an Initial Offering of Multiple Survey Response Options on Response Rates; 2016; Steele, E. A.; Marlar, J.; Allen, L.; Kanitkar, K. N.
- How to Invite? Methods for Increasing Internet Surv ey Response Rate ; 2016; Huang, A. R.; Noel, H.; Hargraves, L.
- Reaching the Mobile Generation: Reducing Web Survey Non-response through SMS Reminders ; 2016; Kanitkar, K. N.; Marlar, J.
- "Don't be Afraid ... We're Researchers!": The Impact of Informal Contact Language...; 2016; Foster, K. N.; Hagemeier, N. E.; Alamain, A. A.; Pack, R.; Sevak, R. J.
- Does Embedding a Survey Question in the Survey Invi tation E-mail Affect Response Rates? Evidence from...; 2016; Vannette, D.
- Communication Channels that Predict and Mediate Self-response ; 2016; Walejko, G. K.
- Ballpoint Pens as Incentives with Mail Questionnaires – Results of a Survey Experiment; 2016; Heise, M.
- Non-Observation Bias in an Address-Register-Based CATI/CAPI Mixed Mode Survey; 2016; Lipps, O.
- Pre-Survey Text Messages (SMS) Improve Participation Rate in an Australian Mobile Telephone Survey:...; 2016; Dal Grande, E.; Chittleborough, C. R.; Campostrini, S.; Dollard, M.; Taylor, A. W.
- Effects of Personalization and Invitation Email Length on Web-Based Survey Response Rates; 2016; Trespalacios, J. H.; Perkins, R. A.
- Assessing targeted approach letters: effects in different modes on response rates, response speed and...; 2016; Lynn, P.
- Refining the Web Response Option in the Multiple Mode Collection of the American Community Survey; 2016; Hughes, T.; Tancreto, J.
- Setting Up an Online Panel Representative of the General Population The German Internet Panel; 2016; Blom, A. G.; Gathmann, C.; Krieger, U.
- Sample Representation and Substantive Outcomes Using Web With and Without Incentives Compared to Telephone...; 2016; Lipps, O.; Pekari, N.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- “Money Will Solve the Problem”: Testing the Effectiveness of Conditional Incentives for...; 2016; DeCamp, W.; Manierre, M. J.
- Effects of Incentive Amount and Type of Web Survey Response Rates; 2016; Coopersmith, J.; Vogel, L. K.; Bruursema, T.; Feeney, K.
- Effect of a Post-paid Incentive on Response to a Web-based Survey; 2016; Brown, J. A.; Serrato, C. A.; Hugh, M.; Kanter, M. H.; A.; Spritzer, K. L.; Hays, R. D.
- Reminder Effect and Data Usability on Web Questionnaire Survey for University Students; 2016; Oishi, T.; Mori, M.; Takata, E.
- Is One More Reminder Worth It? If So, Pick Up the Phone: Findings from a Web Survey; 2016; Lin-Freeman, L.
- Take the money and run? Redemption of a gift card incentive in a clinician survey. ; 2016; Chen, J. S.; Sprague, B. L.; Klabunde, C. N.; Tosteson, A. N. A.; Bitton, A.; Onega, T.; MacLean, C....
- The effect of email invitation elements on response rate in a web survey within an online community; 2016; Petrovcic, A.; Petric, G.; Lozar Manfreda, K.
- A reliability analysis of Mechanical Turk data; 2016; Rouse, S. V.
- Doing Surveys Online ; 2016; Toepoel, V.
- A Privacy-Friendly Method to Reward Participants of Online-Surveys; 2015; Herfert, M.; Lange, B.; Selzer, A.; Waldmann, U.
- Incentive Types and Amounts in a Web-based Survey of College Students; 2015; Krebs, C.; Planty, M.; Stroop, J.; Berzofsky, M.; Lindquist, C.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.