I am sometimes consulted by my peers (MDs) regarding statistical and methodological advice for their research projects. I always suggest they consult a real statistician. For logistical reasons, that advice is not very helpful. I often end up helping in some way. I’m in an unfortunate transition phase in my applied statistical skills, in which I have read enough to know that some approaches consistently produce biased results, but I am unable to provide a convincing argument against using them.
Could the datamethods.org community provide links to papers which address common statistical errors and systematically explain why they produce biased results? This would be very helpful in general. Specifically, I am repeatedly confronted with researchers who would like to use automated variable selection procedures and have trouble convincing them that it is a bad idea.