Web Survey Bibliography
Title Response Mode and Bias Analysis in the IRS’ Individual Taxpayer Burden Survey
Author Brick, J. M., Contos, G.,Masken, K.,Nord, R.
Source Proceedings of the Section, American Statistical Association, 2009
Year 2009
Access date 08.09.2010
Abstract
The Internal Revenue Service (IRS) conducted a survey of taxpayers to better understand the pre-filing and filing burden of individual taxpayers. The sampling frame was taxpayers who filed a 2007 income tax return in 2008. The overall response rate was 48% with roughly 39% of the responses via telephone, 28% via web, and 33% via mail.
In this paper we explore the differences in respondents by response mode, with particular interest in those who responded via the web as the rate for this mode was unexpectedly high. We also address the nonresponse bias and explore ways to adjust for this bias when the researcher is interested in a vector of estimates, not just one point estimate. For this study, total burden is the sum of seven separate but correlated estimates. Since we are able to link the survey responses back to the tax return, we have an especially rich data set to analyze.
Access/Direct link
Proceedings of the Survey Research Methods Section, ASA (abstract) / (full text)
Year of publication2009
Bibliographic typeConference proceedings
Web Survey Bibliography - 2009 (625)
- Statistical disclosure control for survey data; 2009; Skinner, C.
- Sampling of populations: methods and applications, 4th Edition; 2009; Levy, P. S., Lemeshow, S.
- Response format effects on measurement of employment; 2009; Thomas, R. K., Dillman, D. A., Smyth, J. D.
- Recovering the scientist-practitioner model: How IOs should respond to unproctored internet testing; 2009; Beaty, J. C. et al.
- Preserving the integrity of online testing; 2009; Burke, E.
- Mobile surveys from a technological perspective; 2009; Pferdekämper, T., Batanic, B.
- MarketTools TrueSample; 2009
- ISO 26362 Access panels in market, opinion, and social research-Vocabulary and service requirements; 2009
- Introduction to meta-analysis; 2009; Borenstein, M. et al.
- Internet alternatives to traditional proctored testing: Where are we now?; 2009; Tippins, N. T.
- Global market research 2009; 2009
- Getting data for (business) statistics: What's new? What's next?; 2009; Snijkers, G.
- From the Editor; 2009; Sackett, P. R.
- Exploring mode effects in a panel survey of new businesses; 2009; Santos, B., DesRoches, D.
- Dirty little secrets of online panels. And how the one you select can make or break your study; 2009
- comScore Media Metrix U.S. Methodlogy. An ARF research review; 2009; Cook, W. A., Pettit, R.
- Computing weights for the American National Election Study survey data; 2009; Debell, M., Krosnick, J. A.
- Cheating on proctored tests: The other side of the unproctored debate; 2009; Drasgow, F., Nye, C. D., Guo, J., Tay, L.
- Can we make official statistics with self-selection web surveys?; 2009; Bethlehem, J.
- Attitudes over time: The psychology of panel conditioning; 2009; Sturgis, P., Allum, N., Brunton-Smith, I.
- Association collaborative effort releases online research definitions, expands membership; 2009
- The Effect of Phrasing Scale Items in Low-Brow or High-Brow Language on Responses; 2009; Blasius, J., Friedrichs, J.
- Question and Questionnaire Design; 2009; Krosnick, J. A., Presser, S.
- Attrition in Consumer Panels; 2009; Tortora, R. D.
- Sample Design for Understanding Society ; 2009; Lynn, P.
- The 2008 Confirmit Annual Market Research Software Survey; 2009; Macer, T.; Wilson, Sheila
- Predicting Tie Strength With Social Media; 2009; Gilbert, E., Karahalios, K.
- A Special Report from the Advertising Research Foundation - The Foundations of Quality Initiative: A...; 2009; Walker, R., Pettit, R., Rubinson, J.
- Social Network Services as Data Sources and Platforms for e-Researching Social Networks; 2009; Ackland, R.
- A Web-Based Tool for Assessing and Improving the Usefulness of Community Health Assessments; 2009; Stoto, M. A., Straus, S. G., Bohn, C., Irani, P.
- The rise of survey sampling; 2009; Bethlehem, J.
- Using an ABS frame to recruit a probability-based online panel; 2009; DiSogra, C.
- Address Based Sampling: How to Do It, Practical Tips; 2009; Dutwin, D.
- Use of Incentives in Survey Research; 2009; Lavrakas, P. J.
- Stochastic properties of the Internet sample; 2009; Getka-Wilczynska, E.
- Continuous Measurement of Musically-Induced Emotion: A Web Experiment ; 2009; Egermann, H., Nagel, F., Altenmueller, E., Kopiez, R.
- Piloting Data Collection via Cell Phones: Results, Experiences, and Lessons Learned; 2009; ZuWallack, R. S.
- E-epidemiology : Adapting epidemiological methods for the 21st century; 2009; Bexelius, C.
- Survey results as incentives in online panels. Unpublished manuscript; 2009; Goeritz, A.
- Computing response metrics for online panels; 2009; Callegaro, M., DiSogra, C.
- Web based survey: an emerging tool; 2009; Srivenkataramana, T., Saisree, M.
- The Use of Online Methodologies in Data Collection for Gambling and Gaming Addictions; 2009; Griffiths, M. D.
- Designing and Implementing a Career Retrospective Web-based Survey of Library and Information Science...; 2009; Morgan, J. C., Marshall, J. G., Marshall, V., Thompson, C.
- Metadata-Driven Survey Design; 2009; Iverson, J.
- Questasy: Online Survey Data Dissemination Using DDI 3; 2009; de Bruijne, M., Amin, A.
- Methodeneffekte von Web-Befragungen: Soziale Erwünschtheit vs. Soziale Entkontextualisierung; 2009; Taddicken, M.
- Response Mode and Bias Analysis in the IRS’ Individual Taxpayer Burden Survey; 2009; Brick, J. M., Contos, G.,Masken, K.,Nord, R.
- Survey Mode Effects in Two Military Surveys; 2009; Yang, M., Falcone, A. E., Milan, L. M.
- Online Print Publications And The Viabiity Of Charging For On Line Content ; 2009; Vogel, J., Lee-LeGassick, K., Shullman, B., D’Amico, T.
- Measuring Internet And Press Audience In The Media Convergence Era. In Search Of A New Paradigm In Researching...; 2009; Pawlak, J., Póltorak, M.