Reference Collection to push back against "Common Statistical Myths"

I’ll leave that for Frank to answer, as this website is his brainchild. I don’t think it’s unreasonable to present a paper from a different field that still addresses a core statistical topic (the examples you cite are good ones). Here is the site description from the home page, so perhaps this can be our guide, though of course there is some judgement in what exactly fits into this:

This is a place where statisticians, epidemiologists, informaticists, machine learning practitioners, and other research methodologists communicate with themselves and with clinical, translational, and health services researchers to discuss issues related to data: research methods, quantitative methods, study design, measurement, statistical analysis, interpretation of data and statistical results, clinical trials, journal articles, statistical graphics, causal inference, medical decision making, and more.

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