Commentary: Should we always deliberately be non-representative?

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Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population (2017, background): “As with all observational studies, it is incumbent upon researchers to acknowledge potential sources of bias that might affect the generalizability of exposure-disease associations on a case-bycase basis, such as residual confounding, reverse causation, and self-selection bias (24, 29).”
Collider scope: when selection bias can substantially influence observed associations (2016, background): “We have also previously argued that because conventional confounding is typically low for single genetic variants, problems of selection bias will be less in this context (10).”
Recruitment via the Internet and Social Networking Sites: The 1989-1995 Cohort of the Australian Longitudinal Study on Women’s Health (2014, unknown): “Also, having a sample of sufficient size and diversity in terms of a range of key characteristics and exposures is an essential attribute for many epidemiological studies [3,8,15].”