River Sampling – a Fishing Expedition: A Non-Probability Case Study by Alexander Murray-Watters, Stefan Zins, Henning Silber, Tobias Gummer, Clemens M. Lechner
The ease with which large amounts of data can be collected via the Internet has led to a renewed interest in the use of non-probability samples. To that end, this paper performs a case study, comparing two non-probability datasets – one based on a river-sampling approach, one drawn from an online-access panel – to a reference probability sample. Of particular interest is the single-question river-sampling approach, as the data collected for this study presents an attempt to field a multi-item scale with such a sampling method. Each dataset consists of the same psychometric measures for two of the Big-5 personality traits, which are expected to perform independently of sample composition. To assess the similarity of the three datasets we compare their correlation matrices, apply linear and non-linear dimension reduction techniques, and analyze the distance between the datasets. Our results show that there are important limitations when implementing a multi-item scale via a single-question river sample. We find that, while the correlation between our data sets is similar, the samples are composed of persons with different personality traits.