Gelman’s recent short post on Relevance of Bad Science for Good Science includes a handy Top10 junk list:
A Ted talkin’ sleep researcher misrepresenting the literature or just plain making things up; a controversial sociologist drawing sexist conclusions from surveys of N=3000 where N=300,000 would be needed; a disgraced primatologist who wouldn’t share his data; a celebrity researcher in eating behavior who published purportedly empirical papers corresponding to no possible empirical data; an Excel error that may have influenced national economic policy; an iffy study that claimed to find that North Korea was more democratic than North Carolina; a claim, unsupported by data, that subliminal smiley faces could massively shift attitudes on immigration; various noise-shuffling statistical methods that just won’t go away—all of these, and more, represent different extremes of junk science.
And the following sobering reminder why we study failures:
None of us do all these things, and many of us try to do none of these things—but I think that most of us do some of these things much of the time.