Web Survey Bibliography
Relevance & Research Question:
Pre-testing survey instruments is a widely accepted method to test a survey before fielding it to the full sample. There are several advantages of pretesting an online survey, e.g., to collect information regarding survey responses or technical problems, to name only a few.
This study addresses the following questions:
(1) Is pre-testing used before fielding the online survey instrument to the full sample?
(2) Does frequency influence the usage of online survey tools and pre-testing?
(3) Are there differences in usage behavior across different areas (e.g. government, academic, non-profit or for-profit)?
(4) How large is the pretest sample?
Methods & Data:
Data has been collected via a web survey among users of LimeSurvey from July 2009 to October 2011. Of 40,663 responders 14,622 answered the question if they ever ran a pre-test or not. Analyses were conducted using descriptive statistics, cross-tabulations and related statistical tests.
Results:
The core result is that pre-testing online surveys before fielding it to the full sample is now an established method:
(1) Around 65.9% of online survey tool users occasionally or always run a trial survey (pre-test) before fielding it to the full sample.
(2) There is a u-shaped significant relationship between usage frequency of online survey tools and conducting a pre-test (…).
(3) The amount of pre-tests is highest among academic users (62.9%) and lowest among governmental users (58.3%).
(4) Around 64.5 percent of online survey tool users conducted a pre-test using a pre-test sample size of between 1 and 100 cases.
Added Value:
The results of this study provide insights to pre-testing online survey tools. Despite the fact that nearly two-third of online survey tool users are running pre-tests with between 1 and 100 participants, there is potential for the remaining one third of customers to improve their quality of online surveys through pre-testing. Overall, this should lead to a higher acceptance of online surveys.
GOR Homepage (abstract)
Web Survey Bibliography - Germany (420)
- Online Survey Participation via Mobile Devices: Findings From Seven Access Panel Studies; 2013; Bosnjak, M., Poggio, T., Funke, F.
- Use of Drag-and-Drop Rating Scales in Web Surveys and Its Effect on Survey Reports and Data Quality; 2013; Kunz, T.
- Online Panels: Recruitment Based on “Hot Topics” – What are the Consequences?; 2013; Andreasson, M., Martinsson, J.
- The Effectiveness of Mailed Invitations for Web Surveys; 2013; Bandilla, W., Couper, M. P., Kaczmirek, L.
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- Cognitive Probes in Web Surveys: On the Effect of Different Text Box Size and Probing Exposure on Response...; 2013; Behr, D., Bandilla, W., Kaczmirek, L., Braun, M.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- The fish model: What factors affect participants while filling in an online questionnaire?; 2013; Mohamed, B., Lorenz, A., Pscheida, D.
- Interview Duration in Web Surveys: Integrating Different Levels of Explanation; 2013; Rossmann, J., Gummer, T.
- The monetary value of good questionnaire design; 2013; Tress, F.
- Technical and methodological meta-information on current practices in online research: A full population...; 2013; Burger, C., Stieger, S.
- Using interactive feedback to enhance response quality in Web surveys. The case of open-ended questions...; 2013; Emde, M., Fuchs, M.
- Reducing Response Order Effects in Check-All-That-Apply Questions by Use of Dynamic Tooltip Instructions...; 2013; Kunz, T., Fuchs, M.
- Slide to ruin data: How slider scales may negatively affect data quality and what to do about it; 2013; Funke, F.
- Measuring wages via a volunteer web survey – a cross-national analysis of item nonresponse; 2013; Steinmetz, S., Annmaria, B.
- Identifying and Mitigating Satisficing in Web Surveys: Some Experimental Evidence; 2013; Blumenstiel, J. E., Rossmann, J.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Online Mixed Mode Surveying using a Responsive Design; 2013; Kissau, K.
- Sensitive Topics in PC and Mobile Web Surveys; 2013; Mavletova, A. M., Couper, M. P.
- Mobile Research Performance: How Mobile Respondents Differ from PC Users Concerning Interview Quality...; 2013; Schmidt, S., Wenzel, O.
- Who responds to website visitor satisfaction surveys?; 2013; Andreadis, I.
- Measuring working conditions in a volunteer web survey; 2013; de Pedraza, P., Villacampa, A.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Prison break: Releasing offline experiments from methodological constraints by transforming them into...; 2013; Förstel, H., Manthei, K., Mohnen, A., Berger, G.
- Comparison of psychometric properties of internet versions of the Marlowe-Crowne Social Desirability...; 2013; Vesteinsdottir, V., Reips, U. -D., Joinson, A. N., Porsdottir, F.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- Research Design as an Influencing Factor for Reliability in Online Market Research; 2013; Wengrzik, J., Theuner, G.
- Ethics, privacy and data security in web-based course evaluation; 2013; Salaschek, M., Meese, C., Thielsch, M.
- 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.
- E-questionnaire in cross-sectional household surveys; 2013; Karaganis, M.
- 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.
- HTML5 and mobile Web surveys: A Web experiment on new input types; 2013; Funke, F.
- 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.
- Beyond methodology - some ethical implications of "doing research online"; 2013; Heise, N.
- Innovation in Data Collection: the Responsive Design Approach; 2013; Bianchi, A., Biffignandi, S.
- 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.
- Rewards - Money for Nothing?; 2013; Cape, P. J., Martin, P.
- 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.
- Timing of Nonparticipation in an Online Panel: The effect of incentive strategies; 2013; Douhou, S., Scherpenzeel, A.
- How Do Lotteries and Study Results Influence Response Behavior in Online Panels?; 2013; Goeritz, A., Luthe, S. C.
- Sample composition discrepancies in different stages of a probability-based online panel; 2013; Bosnjak, M., Haas, I., Galesic, M., Kaczmirek, L., Bandilla, W., Couper, M. P.
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- Online Questionnaires: Development of ‘basic requirements’; 2012; Tries, S., Blanke, K.
