Web Survey Bibliography
Transportation is an important part of urban policy and precise knowledge about the population’s travel practices is needed in order to develop sustainable transport policies. However, the increasing ‐selection or a selection decision by the study managers. When mixed survey modes are used, individuals choose to belong to one group or another or only respond if the proposed medium suits them. The responses are therefore not comparable, because the sample is no longer random and the presence of respondents is determined by external factors which may also affect the variable of interest in the studied model. This type of selection bias has received considerable coverage in the literature, from both theoretical and empirical standpoints, but as yet little attention has been paid to it with regard to transport surveys. ‐to‐face household travel survey, that is to say individuals who refused to allow an interviewer into their home or who could not be contacted during the first wave of interviews. The results of this survey show that Internet respondents travelled less than the respondents to the face‐to‐face survey. This result subsists even when we limit the socio‐economic differences between the two samples. The comparative analysis is fairly complex as it had to attempt to distinguish between three effects. First, the effect of socioeconomic differences between the Internet respondents and the standard respondents (who answered the face‐to‐face household travel survey), second the effect of any differences in travel between Internet respondents and face‐to‐face respondents, and, third, the effect of differences that were merely due to the survey medium and that did not reflect behavioural differences. It is highly likely that the socioeconomic characteristics and the travel behaviours of the individuals who respond using the Internet are different from those of the individuals who respond to a face‐to‐face interview. To take analysis further, it is necessary to apply econometric techniques that are used for qualitative variables. The sample selection model, whose parameters must be estimated using the two‐stage procedure developed by Heckman provide a promising avenue as, for example, it allows us to isolate the effect on daily travel of socio‐economic differences from that of survey mode. The first stage consists of estimating the survey medium “choice” equation using a probit model. The second stage consists of explaining the differences in travel behaviour using a specific model.
difficulty of obtaining representative data for the target population and the growing complexity of the data that are needed to feed increasingly sophisticated models mean that it is generally not possible to collect all the necessary data in the course of a single survey or with a single method. Combining different data sources has become an extremely important way of increasing knowledge about behaviours and how they are changing as well as improving transport models.
But proposing several data collection modes or methods carries a risk. The collection of information from different sources may provide results that lack comparability. The danger when databases are merged is that a sample selection bias will be created that will compromise the accuracy of explanatory models of travel behaviours. In practice, the selection bias has two sources. It results either from respondent self
The Laboratoire d’Economie des Transports has conducted an Internet survey of no respondents to the 2006 Lyon face
The object of this article is to show that survey mode has an impact on the mobility pattern of respondents. We first present the explanatory variables available for the analysis and estimate an equation of mobility which does not take into account the selection bias. Theoretical developments relative to selection bias follow. Finally, we propose an econometric model that takes into account the selection bias, applied to Lyon household travel survey data.
Conference homepage (abstract)
Web Survey Bibliography - Other CASIC (544)
- Long-Term Efficacy of Sequential Mixed-Mode Designs on Response Rates and Cost in a Panel Survey; 2010; Levenstein, R. M., Barber, J. S., Gatny, H. H.
- Completing Web Surveys on Smart Phones; 2010; Dayton, J. J., Freedner, N., Hannah, K.
- Statistical foundations of cell-phone surveys; 2010; Wolter, K., Smith, P., Blumberg, S. J.
- Self-administered mobile surveys: Usability and (non)participation; 2010; Scherrer, S., Bosnjak, M.
- The impact of incentives and interview methods on response quantity and quality in diary- and booklet...; 2010; Bonke, J., Fallesen, P.
- Computer Literacy and the Accuracy of Substance Use Reporting in an ACASI Survey; 2010; Johnson, T. P., Fendrich, M., Mackesy-Amiti, M. E.
- A report on the 2009 Globalpark Market Research Software Survey; 2010; Macer, T., Wilson, S.
- Web-based versus paper-based data collection for the evaluation of teaching activity: empirical evidence...; 2010; Lalla, M., Ferrari, D.
- Understanding the Willingness to Participate in Mobile Surveys: Exploring the Role of Utilitarian, Affective...; 2010; Bosnjak, M., Metzger, G., Graef, L.
- Mode and Context Effects in Measuring Household Assets; 2010; van Soest, A., Kapteyn, A.
- Improving the response rate and quality in Web-based surveys through the personalization and frequency...; 2010; Muñoz-Leiva, F., Sánchez-Fernández, J., Montoro-Ríos, F. J., Ibáñez-Zapata, J. A.
- College Experiences Survey: Methodological Summary. Final Report; 2009; DesRoches, D., Hall, J. W., Santos, B.
- Cell Phone Mainly Households: Coverage and Reach for Telephone Surveys Using RDD Landline Samples; 2009; Boyle, J., Lewis, F., Tefft, B.
- Cell-Phone-Only Voters in the 2008 Exit Poll and Implications for Future Noncoverage Bias ; 2009; Mokrzycki, M., Keeter, S., Kennedy, C.
- Zero Banks: Coverage Error and Bias in Rdd Samples Based on Hundred Banks with Listed Numbers ; 2009; Boyle, J., Bucuvalas, M., Piekarski, L., Weiss, A.
- National Surveys Via RDD Telephone Interviewing vs. the Internet: Comparing Sample Representativeness...; 2009; Chang, L. C., Krosnick, J. A.
- Best practices in mobile research; 2009; Zahariev, M., Ferneyhough, C., Ryan, C.
- Mobile interviewing; 2009; Lavine, S.
- A comparison of web-based and telephone surveys for assessing traffic safety concerns, beliefs, and...; 2009; Beck, K. H., Yan, A. F., Qi Wang, M.
- The Coverage Bias of Mobile Web Surveys Across European Countries ; 2009; Fuchs, M., Busse, B.
- Item non-response rates: a comparison of online and paper questionnaires ; 2009; Denscombe, M.
- Using mobile phones for survey research A comparison with fixed phones ; 2009; Vicente, P., Reis, E., Santos, R.
- A Comparison of Different Survey Periods in Online Surveys of Persons with Eating Disorders and Their...; 2009; Wesemann, D., Grunwald, A., Grunwald, M.
- A Comparison of Web-Based and Paper-Based Survey Methods Testing Assumptions of Survey Mode and Response...; 2009; Greenlaw, C., Brown-Welty, S.
- Doing Research in the Real World; 2009; Gray, D. E.
- Conducting Mobile Surveys: A Hands-on Introduction to an Innovative Research Mode; 2009; Pferdekämper, T., Melcher, T.
- An experimental mixed mode design on a general population survey ; 2009; Eva, G.
- Does Response Rate Matter? Journal Editors Use of Survey Quality Measures in Manuscript Publication...; 2009; Carley-Baxter, L. R., Hill, C., Roe, D. J., Twiddy, S. E., Baxter, R. K., Ruppenkamp, J.
- Declining Working Phone Rates Impact Sample Efficiency; 2009; Piekarski, L.
- Using Non-Probability Samples for Confusion Surveys - Mall Intercepts and the Internet; 2009; Ericksen, E. P.
- Using Debit Cards for Incentive Payments: Experiences of a Weekly Survey Study; 2009; Gatny, H. H., Couper, M. P., Axinn, W., Barber, J. S.
- Characteristics of Cell Phone Only, Listed, and Unlisted Telephone Households; 2009; Tarnai, J., , Schultz, R.Moore, D.
- Cell Phone-Only Households: A Good Target for Internet Surveys?; 2009; Bates, N.
- Nonsampling Error Research in Practice; 2009; Brick, J. M., Kalton, G.
- Envisioning the Survey Interview of the Future ; 2009; Conrad, F. G., Schober, M. F.
- Are telephone Surveys a dying bread. How declining response rates can be explained and resolved; 2009; Degen, M., Obermüller, A., Schielicke, A.-M.
- Factors Contributing to Participation in Web‐based Surveys among Italian University Graduates; 2009; Cimini, C., Girottu, C., Gasperoni, G.
- Integration of different data collection techniques using the propensity score; 2009; Camillo, F., Conti, V., Ghiselli, S.
- Mode effects in Switzerland: non‐response and measurement error on the European Social Survey; 2009; Roberts, C.
- The mixing of survey modes: application to Laon web and face‐to‐face household travel survey...; 2009; Bayart, C., Bonnel, P.
- An innovative open source strategy for the development of electronic questionnaires for statistical...; 2009; Degortes, M., Landriscina, M., Murgia, M.
- Response rates in multi actor surveys; 2009; Pasteels, I., Ponnet, K., Mortelmans, D.
- Unit non‐response in panel surveys: empirical finding from an experiment; 2009; Haunberger, S.
- Do cash incentives helps with RDD studies? Examination of results from a national and a statewide survey...; 2009; Miller, Y., Barger, K., Hearn, D.
- The Potential of a Multi-mode Data Collection Design to Reduce non-response bias. The Case of a Survey...; 2009; Sala, E., Lynn, P.
- Are people sharing their mobile phones? Selection probabilities in cellular telephone surveys; 2009; Fuchs, M., Busse, B.
- New developments in survey methodology for official statistics; 2009; Bethlehem, J.
- Survey cooperation: response to initial and follow-up requests - Recent experiences from the recruitment...; 2009; Bartsch, S., Engel, U., Schnabel, C., Vehre, H.
- Using Mobile Phones to Administer a Working Memory Updating Task in a Survey - Cognitive Performance...; 2009; Schmiedek, F., Riediger, M., Lindenberger, U., Wagner, G. G.
- Accessibility of individuals for mobile phone surveys; 2009; Gabler, S., Häder, S.