Web Survey Bibliography
The popularity of mixed mode survey designs has led to an increased interest in mode preference. Previous research has shown that offering respondents their preferred mode can increase response rates (Olson, Smyth and Wood 2009), but the effect of mode preference on the quality of survey measurement is still unexplored. In this paper, we examine a variety of experimental questionnaire design manipulations, evaluating whether the quality of data from those who received their preferred mode is better than data quality for those who did not receive their preferred mode. Respondents were asked about their preferred mode and willingness to be recontacted in a 2008 survey, and those that agreed were surveyed again in 2009. The 2009 Quality of Life in a Changing Nebraska survey (n=565, AAPORRR2=46%) randomly assigned respondents to mail or web modes, and one of two questionnaires. The two questionnaires systematically varied many elements of questionnaire design (i.e. question order, text box labels, forced choice vs. check all that apply). Almost one quarter (24%) of the respondents were matched with their stated preferred mode from the previous year. Preliminary analyses indicate significant differences in data quality between those who received and did not receive their preferred mode. In particular, respondents who received their preferred mode had few significant differences in the rate of endorsement of items in a check-all versus forced choice format. In contrast, respondents who did not receive their preferred mode were more likely to endorse statements when presented with a forced choice format than with a check–all format, consistent with previous literature even after controlling for respondent characteristics. These findings may indicate better cognitive processing in a check-all format when respondents receive the mode they prefer. Results provide insight into the impact of mode preference on commonly used questionnaire design features.
Conference Homepage (abstract)
Web Survey Bibliography - 2012 (520)
- Tracking preference expression (DNT); 2012
- The smartphone psychology manifesto; 2012; Miller, G.
- The rise of the "connected viewer"; 2012; Smith, A., Boyles, J. L.
- The practice of social research; 2012; Babbie, E. R.
- The integration of facebook into class management: an exploratory study; 2012; Chou, P. N.
- The effects of item saliency and question design on measurement error in a self-administered survey; 2012; Stern, M. J., Smyth, J. D., Mendez, J.
- The cross platform report. Q2 -2012 - US; 2012
- Speed (necessarily) doesn’t kill: A new way to detect survey satisficing; 2012; Garland, P. et al.
- Smartphone ownership update: September 2012; 2012; Rainie, L.
- Sensitive topics in PC Web and mobile web surveys: Is there a difference?; 2012; Mavletova, A. M., Couper, M. P.
- Selection bias of internet panel surveys: A comparison with a paper-based survey and national governmental...; 2012; Tsuboi, S. et al.
- Screenwise panel: Frequently Asked Questions; 2012
- Research company spotlight - Mobile surveys; 2012
- Redeveloping the research section of Meningitis UK's website — A case study report; 2012; Witt, J. et al.
- Quality in market research. From theory to practice. 2nd Edition; 2012; Harding, D., Jackson, P.
- Participation of mobile users in traditional online studies; 2012; Jue, A.
- Online survey statistics for the mobile future. Updated with Q3 2012 data; 2012
- Ofcom technology tracker Wave 3; 2012
- Ofcom technology tracker Wave 2; 2012
- Not just playing around; 2012; Ewing, T.
- Norme di qualita' Assirm (Assirm quality rules]; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- MRS Guidelines for online reseach; 2012
- More dirty little secrets of online panel research.; 2012
- Mobile email opens report 2nd half 2011; 2012
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.
- Media tracker; 2012
- Measuring the quality of governmental websites in a controlled versus an online setting with the ‘...; 2012; Elling, S. et al.
- Measuring modern media consumption; 2012; Arini, N.
- ISO 20252. Market, opinion and social research-Vocabulary and service requirements, 2nd Edition; 2012
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- Internet use in households and by individual in 2012. Eurostat Statistics in Focus 50/2012; 2012; Seybert, H.
- Internet access - Households and individuals, 2012 part 2; 2012
- Internet access - Households and individuals, 2012; 2012
- Guide to social science data preparation. Best practice throughout the data life cycle; 2012
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- GMI Pinnacle; 2012
- Global market research 2012; 2012
- Flowing with the mainstream. Is mobile market research finally living up to the hype?; 2012; Townsend, L.
- Explaining rising nonresponse rates in cross-sectional surveys; 2012; Brick, J. M., Williams, D.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012
- Online Surveys 2.0; 2012; Elferink, R.
- The Impact of Academic Sponsorship on Online Survey Dropout Rates; 2012; Allen, P. J., Roberts, L. D.
- Especially for You: Motivating Respondents in an Internet Panel by Offering Tailored Questions; 2012; Oudejans, M.
- Social media as a data collection tool: the impact of Facebook in behavioural research; 2012; Zoppos, E.
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.
- Snowball Sampling in Online Social Networks; 2012; Raissi, M., Ackland, R.
- The Use of Facebook as a Locating and Contacting Tool; 2012; McCarthy, T.
- How Often Do You Use the App with a Bird on It? Exploring Differences in Survey Completion Times, Primacy...; 2012; Buskirk, T. D.
- Data quality of questions sensitive to social-desirability bias in web surveys; 2012; Lozar Manfreda, K., Zajc, N., Berzelak, N., Vehovar, V.
