What paradata can tell you about the quality of web surveys?
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The document discusses the role of paradata in evaluating the quality of web surveys, defining paradata as information about the survey response process. It categorizes paradata into direct types, such as contact info and device type, and indirect types, including eye tracking and video recording, while emphasizing the importance of analyzing paradata for improving survey design. Additionally, it highlights ethical considerations and the growing technological capabilities in collecting paradata, noting that while they are useful, they should not replace traditional pretesting methods.
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What paradata can tell you about the quality of web surveys?
- 1. What paradata can tell you about the quality of web surveys? Mario Callegaro Ph.D. Senior Survey Research Scientist User Insights team, Brand Studio Google London Qualtrics Converge Europe, London April 26, 2017
- 2. Disclaimer The opinions expressed in this presentation are the author's own and do not reflect the views of Google 2
- 3. How do we know if a question works? How do we know if a question measures what is intended to measure? How do we know if respondents understand the question and can appropriately respond to it? 3
- 4. What are paradata? Paradata are data about the process of answering the survey itself
- 5. Taxonomy of paradata types Paradata for web surveys can be classified into the following groups: 1. Direct paradata • Contact-info • Device-type paradata • Questionnaire navigation paradata 2. Indirect paradata • E.g. eye tracking, video recording, behavioral coding 5
- 7. Direct paradata: Contact info • Outcomes of an email invitation • Access to the questionnaire introduction page • Last question answered before breakoff 7
- 8. Survey breakoffs by question 8 (Sakshaug & Crawford, 2010) Data courtesy from Sakshaug 75 80 85 90 95 100 Permission asked to use school records (grades) for research purposes
- 10. Direct paradata: Device type • User-agent string • Screen resolution • Browser window size • Javascript and Flash active • IP Address (mostly considered Personal Identifiable Information) • GPS coordinates (mostly considered Personal Identifiable Information) • Cookies 10
- 11. Device type: GPS coordinates example 11Dayton, J & H. Driscoll: The Next CAPI Evolution - Completing Web Surveys on Cell-Enabled iPads. AAPOR
- 12. Device type: GPS coordinates example (cont.) 12Dayton, J & H. Driscoll: The Next CAPI Evolution - Completing Web Surveys on Cell-Enabled iPads. AAPOR 2011
- 14. Direct paradata: Questionnaire navigation 1 Mouse clicks and mouse coordinates Mouse clicks and its position can be captured with a JavaScript. Excessive mouse movements can be a sign of problems with the question Change of answers Change of answers is an indicator of potential confusion with a question and can be used to improve questionnaire design Typing and keystrokes Typing and keystrokes can create an audit trail for each survey and used to detect unusual behavior both from the respondent side and the interviewer side 14
- 15. Questionnaire navigation paradata example lXNtoilre7_2|1|M677|13|1320# M548|174|830# M160|101|1750# M366|192|550# M728|4|7690# M489|247|610# C493|229|3301# R110|1# C493|280|4301# R110|3# C493|345|3901# R110|5# C521|399|3801# SU521|399|60|undefined#| 15 Stieger and Reips (2010, p. 1490)
- 16. Change of answers ex. (Haraldsen et al, 2005) 16
- 17. Fully labeled vs. polar point vs. polar point with numbers vs. answer box 17 Stern (2008, p. 384)
- 18. Fully labeled vs. polar point vs. polar point with numbers vs. answer box Mean ratings 18 2 2 2 3 1 2 3 4 5 Fully labeled Polar point Polar point w/#'s Answer box Stern (2008) & Christian (2003)
- 19. Fully labeled vs. polar point vs. polar point with numbers vs. answer box % of reciprocal changes 19 2 7 6 8 0 2 4 6 8 10 Fully labeled Polar point Polar point w/ #'s Answer box Stern (2008)
- 21. Direct paradata: Questionnaire navigation 2 Order of answering In a page with multiple questions the order of answering is an indicator on how the respondent reads the questions Movements across the questionnaire (forward/backward) If the questionnaire allows going backward or going forward by skipping questions, unusual movements are a symptom of issues with the questionnaire or the respondent Scrolling The amount of scrolling depends on the screen size of the device used and on the size of the browser window used by the respondent 21
- 22. Time latency paradata Time spent per question/screen This is the most published topic in paradata research: time latency information. There are many studies focusing on major themes: • Attitude strength • Response uncertainty • Question wording • Response error (e.g. speeding) • Satisficing / Optimizing 22
- 23. Order of response categories: Positive vs. negative orientation POSITIVE How accessible have your instructors been both in and outside of class? Very accessible Somewhat accessible Neutral Somewhat inaccessible Very inaccessible Don’t know 23 NEGATIVE How accessible have your instructors been both in and outside of class? Very inaccessible Somewhat inaccessible Neutral Somewhat accessible Very accessible Don’t know Christian, Parsons & Dillman (2009)
- 24. Positive vs. negative orientation Results in % 24 0 10 20 30 40 50 Positive order Negative order Christian, Parsons & Dillman (2009)
- 25. Positive vs. negative orientation Time spent answering the question 25 0 0.4 0.8 1.2 1.6 2 2.4 Positive order Negative order Christian, Parsons & Dillman (2009)
- 26. Privacy and ethical issues in collecting paradata Should we tell respondents we are collecting paradata? What happens when we tell respondents we are collecting paradata and we ask permission to use them? • 59.5% agreed in the LISS Dutch panel (across experimental manipulations) • 65.6% agreed in the Knowledge Networks U.S. panel (across experiment manipulations) • 69.3% agreed in a U.S. volunteer non-probability panel (across experimental manipulations) (Couper and Singer, 2013, studies done using vignettes) 26
- 28. Conclusions on paradata • The amount of paradata that can be collected grow as the technological capabilities grow • Although paradata can be collected “easily” and at a low cost, we should not underestimate the cost of managing and analysing paradata (Nicolaas, 2011) • Paradata should not replace other ways of pretesting the questionnaire because it does not answer all the research questions • Paradata analysis is another tool to use in assessing the quality of a survey and in making improvements to the questionnaire and the entire online survey experience 28
- 29. References on Paradata for web surveys Callegaro, M. (2013). Paradata in web surveys (Chapter 11). In F. Kreuter (Ed.), Improving surveys with paradata: Analytic use of process information (pp. 261–279). Hoboken, NJ: Wiley. PDF available at http://research.google.com/pubs/MarioCallegaro.html Callegaro, Lozar Manfreda & Vehovar (2015). Web survey methodology. London: Sage 29
- 30. 30 Q & A