Web Survey Bibliography
The UK Office for National Statistics (ONS) is moving its business and social surveys, and the Census, to electronic modes of data collection. This focus on electronic data collection (EDC) has presented opportunities to access additional data; namely paradata.
Paradata are automatic data collected about the survey data collection process, captured during EDC, and include call records, interviewer observations, time stamps, and other data captured during the process.
Analysis of paradata supports continuous improvement of questionnaires and the wider services that support them. Analysis of paradata and follow-up of respondents to whom the paradata relate could reduce the time and cost burden on those responding.
During an online pilot of one of ONS’ business surveys, the analysis of paradata assisted in the identification of issues with the questionnaire and associated processes for completion. In one case of interest, a respondent showed a pattern of moving through the survey; reaching the last question; exiting; and then, at a later date, going back through all questions, before submitting.
Matching the respondent to call centre records, it was found that they had called to request a specimen questionnaire. This was to enable the respondent to collate the data required to complete the questionnaire. The only way of previewing the questions, otherwise, was to enter false data to bypass validation. This insight demonstrated how ONS could reduce response burden by providing an option to preview the questionnaire up-front. Solutions will be designed and tested before implementation.
This presentation will discuss case study examples, which demonstrate the value of paradata analysis in improving data quality and reducing response burden. Plans to recruit respondents to take part in follow-up research will also be discussed, along with associated ethical considerations concerning data-linkage. It is planned that semi-structured interviews will be used to examine the reasons behind interesting paradata; and experiences of registering for and completing the survey online.
Web survey bibliography - European survey research associaton conference 2017, ESRA, Lisbon (26)
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- 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.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- A test of sample matching using a pseudo-web sample; 2017; Chatrchi, G., Gambino, J.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
- Nonprobability sampling as model construction; 2017; Mercer, A. W.