Web Survey Bibliography
Title Quantitative testing of the most effective advance communication strategies for a mixed mode (including online) UK Labour Force Survey
Author Phelps, A.
Year 2017
Access date 08.09.2017
Abstract With the rise of available web services more generally, the UK public have come to expect to be able to engage with government via digital channels. The UK government is very aware of this demand and has in turn established the Government Digital Service (GDS) which is leading the digital transformation of government.
Over the last decade ONS has conducted numerous qualitative and quantitative investigations into online questionnaire development for Social Surveys and successfully implemented an online completion mode for the 2011 Census. Previous research and past experience has highlighted the need for an extensive research programme to support successful introduction of online data collection, looking at the short and long term opportunities and goals.
The Data Collection Transformation Programme at ONS will transform ONS data collection into a more dynamic and efficient model, maximising the use of non-survey data sources and digital by default collection of data in the production of National and Official Statistics. For Social Surveys this means that ONS needs to deliver a redesigned social statistics model, as well as transformed end-to-end systems.
ONS conducts a number of UK household surveys that feed into a number of important National Statistics indicators. The largest survey that ONS conducts is The Labour Force Survey (LFS) (and sample boost), which is the largest UK household survey, resulting in around 400,000 productive household interviews per annum. The survey is used to produce a range of high profile cross-sectional and longitudinal labour market and Annual Population Survey datasets that are widely used for analysis and publications in the UK and Europe, including for the monthly estimates of labour market supply (including estimates of change in the employment and unemployment rates). The survey is currently governed by European Regulations.
Currently the survey is being redesigned to enable multi-mode data collection and specifically to enable on-line data collection. Qualitative development methodologies have been used by survey methodologists at ONS to elicit the best advance survey documentation and LFS question wording to suit online collection.
ONS is now quantitatively testing the most effective advance documentation strategies via a series of large scale online surveys using revised LFS question wording. The testing work will establish the optimal way of introducing an online LFS survey to the general public.
This presentation set out plans for ongoing quantitative research. It will discuss some of the research findings and challenges faced to date and those that we foresee to be on the horizon. We invite discussion and encourage others to share their experiences and recommendations with us.
Over the last decade ONS has conducted numerous qualitative and quantitative investigations into online questionnaire development for Social Surveys and successfully implemented an online completion mode for the 2011 Census. Previous research and past experience has highlighted the need for an extensive research programme to support successful introduction of online data collection, looking at the short and long term opportunities and goals.
The Data Collection Transformation Programme at ONS will transform ONS data collection into a more dynamic and efficient model, maximising the use of non-survey data sources and digital by default collection of data in the production of National and Official Statistics. For Social Surveys this means that ONS needs to deliver a redesigned social statistics model, as well as transformed end-to-end systems.
ONS conducts a number of UK household surveys that feed into a number of important National Statistics indicators. The largest survey that ONS conducts is The Labour Force Survey (LFS) (and sample boost), which is the largest UK household survey, resulting in around 400,000 productive household interviews per annum. The survey is used to produce a range of high profile cross-sectional and longitudinal labour market and Annual Population Survey datasets that are widely used for analysis and publications in the UK and Europe, including for the monthly estimates of labour market supply (including estimates of change in the employment and unemployment rates). The survey is currently governed by European Regulations.
Currently the survey is being redesigned to enable multi-mode data collection and specifically to enable on-line data collection. Qualitative development methodologies have been used by survey methodologists at ONS to elicit the best advance survey documentation and LFS question wording to suit online collection.
ONS is now quantitatively testing the most effective advance documentation strategies via a series of large scale online surveys using revised LFS question wording. The testing work will establish the optimal way of introducing an online LFS survey to the general public.
This presentation set out plans for ongoing quantitative research. It will discuss some of the research findings and challenges faced to date and those that we foresee to be on the horizon. We invite discussion and encourage others to share their experiences and recommendations with us.
Access/Direct link Conference Homepage (abstract) / (presentation)
Year of publication2017
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography (4086)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Mind the Mode: Differences in Paper vs. Web-Based Survey Modes Among Women With Cancer; 2017; Hagan, T. L.; Belcher, S. M.; Donovan, H. S.
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Lessons from recruitment to an internet based survey for Degenerative Cervical Myelopathy: merits of...; 2017; Davies, B.; Kotter, M. R.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Examining Factors Impacting Online Survey Response Ratesin Educational Research: Perceptions of Graduate...; 2017; Saleh, A.; Bista, K.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- 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.
- 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.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.