Key points are not available for this paper at this time.
Social scientists rely heavily on data collected from human participants via surveys or experiments. To obtain these data, many social scientists recruit participants from opt-in online panels that provide access to large numbers of people willing to complete tasks for modest compensation. In a large study (total N=13,053), we explore nine opt-in non-probability samples of American respondents drawn from panels widely used in social science research, comparing them on three dimensions: response quality (attention, effort, honesty, speeding, and attrition), representativeness (observable demographics, measured attitude typicality, and responding to experimental treatments), and professionalism (number of studies taken, frequency of taking studies, and modality of device on which the study is taken). We document substantial variation across these samples on each dimension. Most notably, we observe a clear tradeoff between sample representativeness and response quality (particularly regarding attention), such that samples with more attentive respondents tend to be less representative, and vice versa. Even so, we find that for some samples, this tension can be largely eliminated by adding modest attention filters to more representative samples. This and other insights enable us to provide a guide to help researchers decide which online opt-in sample is optimal given one’s research question and constraints.
Stagnaro et al. (Thu,) studied this question.