Web Survey Bibliography
Title Mixing Modes: Challenges (and Tradeoffs) of Adapting a Mailed Paper Survey to the Web
Year 2016
Access date 09.06.2016
Abstract
Recent trends show that survey respondents are increasingly difficult and expensive to reach. Methodology research consistently demonstrates that
tailored and adaptive designs may offer the best solution for collecting high-quality data. One strategy that can increase coverage and representativeness — and potentially reduce cost — uses sequential mix
ed-mode designs that include a web-based response component. In January 2016, the National Center for Education Statistics will test a sequential mixed-mode, web-push design for the 2016 administration of the National Household Education Survey (NHES). For several cycles, the NHES has used an address-based sample to administer a two-phase, self-
administered mailed questionnaire in which sampled households are rostered using a phase-1 screener and then a single individual is sampled from responding households to complete a longer phase-2 “topical” survey. This presentation will describe the process of adapting the two-phase paper design to incorporate a variable-phase web survey, and some of the key challenges faced while transitioning from a well-tested paper-only to a mixed-mode administration. Authors will describe the tradeoffs between maintaining consistency with the paper instrument and optimizing the web survey; the complexity of building a web instrument that in some situations (e.g., single-adult households) must be a single-phase survey with both phases completed by one individual, while other situations require a different respondent to complete each phase; and the intricacies of using phase-1 screener data to customize wording in both English and Spanish using known information about the respondent. In addition to discussing the above challenges and proposed solutions, the paper will present selected results of usability testing and the resulting design changes to the web instrument. This study contributes to the growing body of research examining the most effective ways to use mixed-mode designs to increase survey response and representativeness while minimizing cost and mode effects in a national household survey.
tailored and adaptive designs may offer the best solution for collecting high-quality data. One strategy that can increase coverage and representativeness — and potentially reduce cost — uses sequential mix
ed-mode designs that include a web-based response component. In January 2016, the National Center for Education Statistics will test a sequential mixed-mode, web-push design for the 2016 administration of the National Household Education Survey (NHES). For several cycles, the NHES has used an address-based sample to administer a two-phase, self-
administered mailed questionnaire in which sampled households are rostered using a phase-1 screener and then a single individual is sampled from responding households to complete a longer phase-2 “topical” survey. This presentation will describe the process of adapting the two-phase paper design to incorporate a variable-phase web survey, and some of the key challenges faced while transitioning from a well-tested paper-only to a mixed-mode administration. Authors will describe the tradeoffs between maintaining consistency with the paper instrument and optimizing the web survey; the complexity of building a web instrument that in some situations (e.g., single-adult households) must be a single-phase survey with both phases completed by one individual, while other situations require a different respondent to complete each phase; and the intricacies of using phase-1 screener data to customize wording in both English and Spanish using known information about the respondent. In addition to discussing the above challenges and proposed solutions, the paper will present selected results of usability testing and the resulting design changes to the web instrument. This study contributes to the growing body of research examining the most effective ways to use mixed-mode designs to increase survey response and representativeness while minimizing cost and mode effects in a national household survey.
Access/Direct link Conference Homepage (abstract)
Year of publication2016
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.