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Web Survey Bibliography

Title A critical review of studies investigating the quality of data obtained with online panels based on probability and nonprobability samples
Year 2014
Access date 30.06.2014
Abstract

This chapter provides an overview of studies comparing the quality of data collected by online survey panels by looking at three criteria: (1) comparisons of point estimates from online panels to high-quality, established population benchmarks; (2) comparisons of the relationship among variables; and (3) the reproducibility of results for online survey panels conducted on probability samples to panels conducted on nonprobability samples. When looking at point estimates, all online survey panels differed to some extent from the population benchmarks. However, the largest comparison studies suggest that point estimates from online panels of nonprobability samples have higher differences as compared to benchmarks than online panels of probability samples. This finding is consistent across time and across studies conducted in different countries. Moreover, post-stratification weighting strategies helped little and in an inconsistent way to reduce such differences for data coming from online panels of nonprobability samples, whereas these strategies did bring estimates from online panels of probability samples consistently closer to the benchmarks. When comparing relationships among variables, it was found that researchers would reach different conclusions when using online panels of nonprobability samples versus panels of probability samples. When looking at reproducibility of results, the limited evidence found suggests that there are no substantial differences in replication and effect size across probability and nonprobability samples for question wording experiments and when comparing students samples to other samples. It is worth noting that in pre-election polls, an area where abundant prior knowledge exists, online panels of nonprobability samples have consistently performed as well and in some cases better than polls based on probability samples in predicting election winners.

Year of publication2014
Bibliographic typeBook section
Print
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