Web Survey Bibliography
Online research has experienced remarkable growth over the past fifteen years. To keep up with demand,some companies have become quite creative. Rather than continuing to rely exclusively on opt-in panelists, for example, they've developed new methods to include non-panelists within online surveys. They've also figured out how to direct or route respondents who do not qualify for one survey to another for which they might. Despite these important advances, the available supply of respondents to which any supplier might have access is insufficient at times for certain kinds of studies,such as a tracking survey of a rare population. To meet the requirements of such studies, researchers now depend heavily on multiple samples sources (e.g.,Panel A,B; River 1). Some evidence suggests,however, that the decision can have unintended consequences. In research carried out in 2008 evaluating seventeen different opt-in panels, for instance,the Advertising Research Foundation found "wide variance,particularly on attitudinal and/or opinion questions (purchase intent,concept reaction, and the like)," even after holding constant socio demographic and other factors (Walker et al., 2009). Since that time,some researchers have mounted new research to understand how to select multiple sample sources for the same survey without increasing bias. Proponents of these approaches cite at least three benefits: (a) consistency (or interchangeability) of new respondent sources with existing ones,(b) complementariness of new respondent sources with existing ones relative to an external standard, and (c) enhanced representativeness relative to the US general population through calibration with non-online data sources. Although these approaches have taken a step in the right direction, we believe they have not gone far enough for three main reasons: (a) they restrict the pool of potential respondents to those from sample sources vetted previously, thereby limiting supply, (b) they seem to assume that the vetted sample sources do not change over time,and (c) they rely on benchmark data sets
that have either limited shelf lives or uncertain external validity. We therefore suspect that they may not produce the same levels of sample representativeness and response accuracy as a new methodology, which we refer to as SmartSelect, that selects potential survey respondents in real-time from either a single sample source or multiple sources based on how well their characteristics match an appropriate, evolving standard with demonstrated evidence of external validity.
CASRO Journal Homepage (Abstract) / (Full text)
Web survey bibliography (4086)
- Approaches to empiric ablation of slow pathway: results from the Canadian EP web survey; 2012; Laish-Farkash, A., Shurrab, M., Tiong, I., Verma, A., Amit, G., Kiss, A., Morriello, F., Singh, S.,...
- Statistical Disclosure Control; 2012; Hundepool, A., Domingo-Ferrer, J., Franconi, L., Giessing, S., Schulte Nordholt, E., Spicer, K., de...
- Methodology of the RAND Continuous 2012 Presidential Election Poll ; 2012; Kapteyn, A., Meijer, E., Weerman, B.
- How and when social media storms impact brands; 2012; Morris, A., Perry, H.
- (Online) Access Panels: Types and Quality Standards; 2012; Bosnjak, M.
- Biting the Hand and Bending the Rules: An IJMR Presentation; 2012; Pettit, A.
- Passive measurement of online data in Practice - A White Paper Wakoopa; 2012
- Using response probabilities for assessing representativity; 2012; Bethlehem, J.
- Analysis of Web Survey Data based on Similarity of Fuzzy Clusters; 2012; Chiba, R., Sato-Ilic, M.
- Disentangling Mode-Specific Selection and Measurement Bias in Social Surveys; 2012; Buelens, B., van der Laan, J., Schouten, B., Klausch, L. T., van der Brakel, J., Burger, J.
- The efficiency and effectiveness of mixed mode versus single mode designs; 2012; Blunsdon, B.
- The National Survey of College Graduates: Developing a Web Data Collection Component; 2012; Thornton, T.
- Automated Web Testing Using Selenium; 2012; Gaston, D., Fanning, S., Daher, L.
- Mixed Mode: Phone and Web Discussion on Efficient Strategies; 2012; Gagnon, M.
- The Measurement of Consistency in Online Research; 2012; Gittelman, S. H., Trimarchi, E.
- Thinking Differently About How to Select Respondents for Surveys; 2012; Terhanian, G., Bremer, J.
- Benefits of Modular Design for Mobile and Online Surveys; 2012; Kelly, F., Johnson, A., Stevens, S.
- Emerging Techniques of Respondent Engagement: Leveraging Game and Social Mechanics for Mobile Application...; 2012; Lai, J. W., Vanno, L.
- An Introduction to Using Video for Research; 2012; Jewitt, C.
- A Machine Learning Based Topic Exploration and Categorization on Surveys; 2012
- Survey Swipe; 2012; Macer, T.
- A Framework for the Collection of Universal Client Side Paradata (UCSP); 2012; Kaczmirek, L.
- Improving ability measurement in surveys by following the principles of IRT: The Wordsum vocabulary...; 2012; Cor, K., Haertel, E., Krosnick, J. A., Malhotra, N.
- Online Surveys Aren't Just for Computers Anymore! Exploring Potential Mode Effects between Smartphone...; 2012; Buskirk, T. D., Andrus, C.
- Why do survey participants choose to report by Web, paper, or not at all? Results from an American Community...; 2012; Nichols, E. M.
- Worldwide online research spending; 2012
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- Using multivariate statistics, 6th Edition; 2012; Tabachnick, B. G., Fidell, L. S.
- Unintentional mobile respondents; 2012; Peterson, G.
- Tracking preference expression (DNT); 2012
- The smartphone psychology manifesto; 2012; Miller, G.
- 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., D., Mendez, J. D.Smyth, J. D.
- The cross platform report. Q2 -2012 - US; 2012
- Smartphone ownership update: September 2012; 2012; Rainie, L.
- Selection bias of internet panel surveys: A comparison with a paper-based survey and national governmental...; 2012; Tsuboi, S., Yoshida, H., Ae, R., Kojo, T., Nakamura, Y., Kitamura, K.
- Screenwise panel: Frequently Asked Questions; 2012
- Research company spotlight - Mobile surveys; 2012
- 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 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.