A smarter way to select respondents for surveys?

Online research has experienced astonishing growth over the past 15 years. To keep up with this growth, researchers have developed new ways of accessing and utilising respondents. Nevertheless, they can still find it difficult to complete the needed number of interviews on time, particularly when the target population is rare or in high demand. For this reason, it is common today for researchers to use more than one sample source for some types of project, such as a tracking survey that measures change over time. Adding one or more sample source to the original might address the need for more respondents, but some evidence suggests that it might also decrease sample representativeness and reduce response accuracy. In this paper, we introduce a new methodology that enables researchers to select potential survey respondents 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. We also present evidence suggesting that, in the aggregate, respondents who are selected through the new methodology are more representative of the target population than respondents selected by other means. Finally, we consider possible implications of the new methodology on methods other than online research with non-probability samples.