Prototypical example: imagine a scientific field in which the large majority of practitioners have a very poor understanding of statistics, p-hacking, etc. Then lots of work in that field will be highly memetic despite trash statistics, blatant p-hacking, etc. Sure, the most competent people in the field may recognize the problems, but the median researchers don’t, and in aggregate it’s mostly the median researchers who spread the memes.
Complicated analysis (like going far beyond p-values) is easy for anyone to see and it is evidence of effort. Complex analysis usually coocurs with thoroughness so fewer mistakes. Complicated analysis coocurs with many concurrent tests so less need to produce positive results so less p-hacking. Consequently, there is a fairly simple solution to researchers with mediocre statistical skills gaining too much trust: more plots! Anyway, I find correlation graphs and multiple comparison impressive. Also I am usually more skilled in data analysis than the subject of a paper so can more easily verify that.
Complicated analysis (like going far beyond p-values) is easy for anyone to see and it is evidence of effort. Complex analysis usually coocurs with thoroughness so fewer mistakes. Complicated analysis coocurs with many concurrent tests so less need to produce positive results so less p-hacking. Consequently, there is a fairly simple solution to researchers with mediocre statistical skills gaining too much trust: more plots! Anyway, I find correlation graphs and multiple comparison impressive. Also I am usually more skilled in data analysis than the subject of a paper so can more easily verify that.