While "p-hacking" is likely more prevalent in certain fields (e.g., psychology) and with experimental (rather than observational) data, such manipulations are becoming increasingly common and pose a real challenge to social science. Excerpts from an interesting post by Jerry Adler (commentary from Althouse here) summarize:
"In 2011, a psychologist named Joseph P. Simmons and two colleagues set out to use real experimental data to prove an impossible hypothesis. Not merely improbable or surprising, but downright ridiculous. The hypothesis: that listening to The Beatles’ “When I’m Sixty-Four” makes people younger. The method: Recruit a small sample of undergraduates to listen to either The Beatles song or one of two other tracks, then administer a questionnaire asking for a number of random and irrelevant facts and opinions—their parents’ ages, their restaurant preferences, the name of a Canadian football quarterback, and so on. The result: By strategically arranging their data and carefully wording their findings, the psychologists “proved” that randomly selected people who hear “When I’m Sixty-Four” are, in fact, younger than people who don’t."
The authors of the "When I'm Sixty-Four" paper "draw attention to a glaring problem with modern scientific protocol: Between the laboratory and the published study lies a gap that must be bridged by the laborious process of data analysis. As Simmons and his co-authors showed, this process is a virtual black box that, as currently constructed, ‘allows presenting anything as significant.’ And if you can prove anything you want from your data, what, if anything, do you really know?”