Web Survey Bibliography
Probability based surveys, those including with samples selected through a known randomization mechanism, are considered by many to be the gold standard in contrast to non-probability samples. Probability sampling theory was first developed in the early 1930’s and continues today to justify the estimation of population values from these data. Conversely, studies using non-probability samples have gained attention in recent years but they are not new. Touted as cheaper, faster (even better) than probability designs, these surveys capture participants through various “on the ground” methods (e.g., opt-in web survey). But, which type of survey is better? This paper is the first in a series on the quest for a quality framework under which all surveys, probability and non-probability-based, may be measured on a more equal footing. First, we highlight a few frameworks currently in use, noting that “better” is almost always relative to a survey’s fit for purpose. Next, we focus on the question of validity, particularly external validity when population estimates are desired. Estimation techniques used to date for non-probability surveys are reviewed, along with a few comparative studies of these estimates against those from a probability-based sample. Finally, the next research steps in the quest are described, followed by a few parting comments.
Web survey bibliography - Valliant, R. L. (4)
- Estimation with Non-probability Surveys and the Question of External Validity; 2015; Dever, J. A.; Valliant, R. L.
- Investigating the Bias of Alternative Statistical Inference Methods in Sequential Mixed-Mode Surveys; 2013; Suzer-Gurtekin, Z., Heeringa, S. G., Valliant, R. L.
- Practical tools for designing and weighting survey samples; 2013; Valliant, R. L., Daver, J. A., Kreuter, F.
- Internet Surveys: Can Statistical Adjustments Eliminate Coverage Bias?; 2008; Dever, J. A., Rafferty, A., Valliant, R. L.