Web Survey Bibliography
Title The Matrix Lives On: Improving Grids for Online Surveys
Author Thomas, R. K.; Barlas, F. M.; Graham, P.; Subias, T.
Year 2015
Access date 16.06.2016
Abstract
In self-administered surveys, grids have evolved to efficiently measure multiple concepts using the same graded response format across a number of different targets, with responses typically in columns and the rating targets to evaluate in rows. Generally, grids allow us to assess multiple targets more quickly than if each target is presented separately. However, grids have a number of issues, and in particular affect respondent experience on mobile devices - measurement in online surveys is generally limited by screen size. In a series of 3 studies with over 80,000 respondents in total, we present experiments that examined how reducing the number of grid response categories affects the measurement of a variety of concepts. We found that response formats with fewer response categories take less time to complete, are easier to complete on mobile platforms, and show as much validity as formats with more response categories. In addition, they also appear to detect smaller differences between rating targets than those with more response categories. This higher level of differentiation was unexpected, and we explore some reasons for this occurrence.
Access/Direct link Joint Statistical Meetings 2015
Year of publication2015
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Graham, P. (6)
- Beyond the Survey: Improving Data Insights and User Experience with Mobile Devices ; 2016; Graham, P.; Lew, G.
- The Matrix Lives On: Improving Grids for Online Surveys; 2015; Thomas, R. K.; Barlas, F. M.; Graham, P.; Subias, T.
- Purposefully Mobile: Experimentally Assessing Device Effects in an Online Survey ; 2015; Barlas, F. M.; Thomas, R. K.; Graham, P.
- What They Can’t See Can Hurt You: Improving Grids for Mobile Devices; 2015; Randall, T. K.; Barlas, F. M.; Graham, P.; Subias, T.
- Using KnowledgePanel® to Improve the Sample Representativeness and Accuracy of Opt-in Panel Data...; 2010; Dennis, J. M., Peugh, J., Graham, P.
- Assessing the Accuracy of Online Panel Research: A Toolkit for Decision Makers; 2008; Graham, P.