Web Survey Bibliography
Analysts working with data generated by different modes of data collection often want to be sure that their measurements are comparable. If a set of questions is designed to measure the same latent trait, confirmatory factor analysis (CFA) is a useful analytic tool for this purpose. It can be applied to assess, whether properties, such as measurement error, the association between latent traits and questions (measurement invariance) and the means of latent traits, are equivalent across survey modes. We illustrate an application using empirical data from an experiment based on a national probability sample, in which 4048 respondents were randomly assigned to either face-to-face, telephone, mail or web interviewing. Two related traits were measured with three questions respectively, “moral support of the police” and the “obligation to obey”, which form the basis of our CFA model. The association between latent traits and questions was invariant across modes. However, measurement errors differed between modes. In particular, the self-administered modes yielded more reliable indicators than the interviewer modes. Moreover, we find systematic bias between modes on the mean of one of the traits. The effect signs suggest that respondents gave socially desirable answers in the intervieweradministered modes. A particularity of survey modes is that sample compositions are often heterogeneous. If the selective process is correlated with model elements, such as traits, it can bias invariance tests and decrease fit. We illustrate available options to adjust for this problem, for example propensity score methods or covariate adjustment, all based on the use of auxiliary variables, such as socio-demographics. In conclusion, self-administered modes seem to produce measurements of lower quality than interviewer-administered modes with respect to random error and systematic bias. Modes may thus affect both, the error variance and bias of an estimate. An effect can be suspected particularly between interviewer and non-interviewer modes.
Conference Homepage (abstract)
Web Survey Bibliography - Noncoverage & sampling (1271)
- How Representative are Google Consumer Surveys?: Results From an Analysis of a Google Consumer Survey...; 2013; Krishnamurty, P., Tanenbaum, E., Stern, M. J.
- Impacts of Unit Nonresponse in a Recontact Study of Youth; 2013; Mendelson, J., Viera Jr., L.
- Changing to a Mixed-Mode Design: The Role of Mode in Respondents’ Decisions About Participation...; 2013; Collins, D., Mitchell, M., Toomes, M.
- Comparing the Effects of Mode Design on Response Rate, Representativeness, and Cost Per Complete in...; 2013; Tully, R.
- Internet Response for the Decennial Census – 2012 National Census Test; 2013; Reiser, C.
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Paradata for Coverage Research ; 2013; Eckman, S.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- Ten questions to ask your online survey provider; 2013; Williams, D.
- Practical tools for designing and weighting survey samples; 2013; Valliant, R. L., Daver, J. A., Kreuter, F.
- Report Of The AAPOR Task Force On Non-probability sampling; 2013; Baker, R. P., Brick, J. M., Bates, N., Battaglia, M. P., Couper, M. P., Dever, J. A., Gile, K. J., Tourangeau...
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys; 2013; Steinmetz, S., Raess, D., Tijdens, K., de Pedraza, P.
- Sampling, Channels, and Contact Strategies in Internet Survey; 2013; Macrì, E., Tessitore, C.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- An approach to selecting online respondents; 2013; Terhanian, G.
- Designing and conducting business surveys; 2013; Snijkers, G.,Araldsen, G., , Willimack, D. K.Jones, J.
- Modular Survey Design: A Bite Size Proposal; 2013; Kelly, F., Stevens, S., Johnson, A.
- Does Sample Size Still Matter?; 2013; Bakken, D. G., Bond, M.
- Solving the Unintentional Mobile Challenge; 2013; Peterson, G., Mechling, J., LaFrance, J., Ham, G.
- Internet-Based Recruitment to a Depression Prevention Intervention: Lessons From the Mood Memos Study...; 2013; Morgan, A. J., Jorm, A. F., Mackinnon, A. J.
- Examination of the equivalence of self-report survey-based paper-and-pencil and internet data collection...; 2013; Weigold, A., Weigold, I. K., Russell, E. J.
- Technical and methodological meta-information on current practices in online research: A full population...; 2013; Burger, C., Stieger, S.
- Mobile Research Performance: How Mobile Respondents Differ from PC Users Concerning Interview Quality...; 2013; Schmidt, S., Wenzel, O.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Research Design as an Influencing Factor for Reliability in Online Market Research; 2013; Wengrzik, J., Theuner, G.
- Seducing the respondent – how to optimise invitations in on-site online research?; 2013; Póltorak, M., Kowalski, J.
- Influence of mobile devices in online surveys; 2013; Maxl, E., Baumgartner, T.
- GESIS Online Panel Pilot: Results from a Probability-Based Online Access Panel; 2013; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.
- Online Survey – Research with children on advertising impact; 2013; Funkenweh, V., Busch, J., Amthor, A. L., Boeer, A., Gaedke, J.
- Metadata on the demographics of online research: Results from a full-range study of available online...; 2013; Burger, C., Stieger, S.
- How the screen-out influence the dropout of a commercial panel; 2013; Bartoli, B.
- Break-off and attrition in the GIP amongst technologically experienced and inexperienced participants...; 2013; Blom, A. G., Bossert, D., Clark, V., Funke, F., Gebhard, F., Holthausen, A., Krieger, U., Wachenfeld...
- Nonresponse and Nonresponse Bias in a Probability-Based Internet Panel; 2013; Blom, A. G., Bossert, D., Funke, F., Gebhard, F., Holthausen, A., Krieger, U.
- Effects of incentive reduction after a series of higher incentive waves in a probability-based online...; 2013; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- Mixed-mode including web: Recent developments at Statistics Netherlands; 2013; Luiten, A., Schouten, B.
- Web coverage in the UK and its potential impact on general population web surveys; 2013; Callegaro, M.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- Participation and engagement in web surveys of the general population: An overview of challenges and...; 2013; Roberts, C.
- Using Web Survey Panels to Estimate Population Characteristics: A Comparison of Alternative Approaches...; 2013; Rivers, D.
- The ONS Beyond 2011 Programme & possible implications for social surveys; 2013; Morris, L.
- Issues of Coverage and Sampling in Web Surveys for the General Population: An Overview; 2013; Lynn, P.
- Use of a Social Networking Web Site for Recruiting Canadian Youth for Medical Research; 2013; Chu, J. L., Snider, C. E.
- The smartphone in survey research: experiments for time use data; 2013; Fernee, H., Scherpenzeel, A.
- Understanding and Applying Research Design; 2013; Abbott, M. L., McKinney, J.
- Large-Scale Analysis and Testing; 2013; Cao, M., Zhang, Q.
- Virtual Research Methods; 2013; Hine, C.
- Surveying “difficult-to-sample” backpackers through Facebook? Employing a mixed-mode dual...; 2013; Morris Paris, C.
