Web Survey Bibliography
At the workshop I will present objectives, procedures and results from a pilot-study.
Background
Conventionally, data editing is initiated subsequent to data collection. The preliminary object of post data collection data editing, is to identify possibly defective data. The object proper is to correct errors and improve data quality. Correction of possible defective data may involve costly manual record checks, burdening re-contact with individual businesses/respondents, and possible bias from automatic imputation and statistical editing. In order to minimise costs and burden, the cut off level for possibly defective input data, which is actually edited, may be set low, resulting in low quality output data.
Pilot survey
Data collection for statistics on Vacant Positions for ESS is fairly non-complex and straight forward - compared to most business statistics at Statistics Denmark. In the questionnaire two questions are asked: Number of vacant positions, and – as a reference variable for data editing - number of persons currently employed. Previously, data editing for this survey was initiated post data collection: For each work unit in the sample, the reported number of vacant positions was compared to the reported number of persons employed. The reported number of employees was also compared to the number of employees recorded in the survey 12 months earlier, and to the number of employees currently recorded for the work unit in the Danish Central Business Register. This was done in order to check, whether the responding businesses had reported vacant positions for the intended work unit (and e.g. not for the whole enterprise). Correction of possible defective data involved manual record checks, re-contact to respondents by phone and statistical imputation and manipulation.
Advanced dynamic online data editing
At Statistics Denmark, Survey and Methods the vacant positions survey was selected as a pilot for “advanced dynamic online data editing”. An online questionnaire was developed, where some of the “old” post data collection edit checks for cross reference were incorporated and run dynamically - as the respondent enters data in the form. The questionnaire for each individual work unit was pre-loaded with: Number of employees recorded in the survey 12 months earlier and number of employees currently recorded in Danish Central Business Register. These values were not actually visible to the respondent in the form, but only used as reference data. If data is entered in the form, which does not comply with the “old” post data collection edit checks, then a warning is generated, and the respondent is asked to re-consider and either modify the response or enter a comment/explanation.
Workshop Homepage (abstract) / (presentation)
Web survey bibliography (457)
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Device and Internet Use among Spanish-dominant Hispanics: Implications for Web Survey Design and Testing...; 2017; Trejo, Y. A. G.; Schoua-Glusberg, A.
- Role of online survey tools in creating temporally accurate Environmental Product Declarations (EPD)...; 2017; Ganguly, I.; Bowers, T.; Pierobon, F.; Eastin, I.
- CAQDAS at a Crossroads: Affordances of Technology in an Online Environment; 2017; Silver, C.; Bulloch, L. S.
- Development and Pilot Test of a Mobile Application for Field Data Collection; 2016; Chiappetta, L.; Kerr, M. M.
- A streamlined approach to online linguistic surveys; 2016; Erlewine, M. Y.; Kotek, H.
- The Effects of Vignette Placement on Attitudes Toward Supporting Family Members; 2016; Lau, C. Q., Seltzer, J. A., Bianchi, S. M.
- Using Web Panels to Quantify the Qualitative: The National Center for Health Statistics Research and...; 2016; Scanlon, P. J.
- Bees to Honey or Flies to Manure? How the Usual Subject Recruitment Exacerbates the Shortcomings of...; 2016; Snell, S. A., Hillygus, D. S.
- The Use of a Nonprobability Internet Panel to Monitor Sexual and Reproductive Health in the General...; 2015; Legleye, S; Charrance, G.; Razafindratsima, N.; Bajos, N.; Bohet, A.; Moreau, C.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Does Sequence Matter in Multimode Surveys: Results from an Experiment; 2014; Wagner, J., Arrieta, J., Guyer, H., Ofstedal, M. B.
- The Use of Cognitive Interviewing Methods to Evaluate Mode Effects in Survey Questions; 2014; Gray, M., Blake, M., Campanelli, P.
- Build your own social network laboratory with Social Lab: a tool for research in social media; 2014; Garaizar, P., Reips, U.-D.
- Using Eye Tracking to Evaluate Email Notifications of Surveys and Online Surveys Collecting Address...; 2014; Olmsted, E. L., Nichols, E. M.
- Correlates of Attrition in the German Internet Panel: Drop-Outs and Sleepers; 2014; Blom, A. G., Beissel-Durrant, G.
- Survey Breakoff in Online Panels; 2014; McCutcheon, A. L.
- Inside the Turk Understanding Mechanical Turk as a Participant Pool; 2014; Paolacci, G., Chandler, J.
- Nonresponse and measurement error in an online panel; 2014; Roberts, C., Allum, N., Sturgis, P.
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Informing panel members about study results; 2014; Scherpenzeel, A., Toepoel, V.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- A critical review of studies investigating the quality of data obtained with online panels based on...; 2014; Callegaro, M., Villar, A., Yeager, D. S., Krosnick, J. A.
- Online panel research: History, concepts, applications and a look at the future; 2014; Callegaro, M., Baker, R., Bethlehem, J., Goeritz, A., Krosnick, J. A., Lavrakas, P. J.
- Motives for joining nonprobability online panels and their association with survey participation behavior...; 2014; Keusch, F., Batinic, B., Mayerhofer, W.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- Does Gamification Work? - A Literature Review of Empirical Studies on Gamification ; 2014; Hamari, J., Koivisto, J., Sarsa, H.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Pret met panels [Fun online]; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- The Future of Social Media, Sociality, and Survey Research; 2013; Hill, C., Dever, J. A.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Social Media, Sociality, and Survey Research; 2013; Hill, C., Dean, E., Murphy, J.
- Investigation of background acoustical effect on online surveys: A case study of a farmers' market...; 2013; Tang, Xi.
- Should the third reminder be sent? The role of survey response timing on web survey results; 2013; Rao, K., Pennington, J.
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson, J.
- Using an Item Response Theory Approach to Measure Survey Mode of Administration Effects: Analysis of...; 2013; Mariano, L. T., Elliott, M. N.