I was heavily encouraged to do what would later be called “p-hacking”, but it looked different from what they describe here. This article describes p-hacks for people that aren’t into math/stats. I always ended up p hacking because I was into stats methods.
Somebody would say “here’s an old dataset that didn’t work out, I bet you can use one of those new stats methods you’re always reading about to find a cool effect!”, and then the fishing expedition takes off.
A couple weeks later you show off some cool effects that your new cutting edge results were able to extract from an old, useless dataset.
But instead of saying “that’s good pilot data, let’s see if it holds up with a new experiment”, you’re told “you can publish that! Keep this up and maybe you’ll be lucky enough to get a job someday!”
Somebody would say “here’s an old dataset that didn’t work out, I bet you can use one of those new stats methods you’re always reading about to find a cool effect!”, and then the fishing expedition takes off.
A couple weeks later you show off some cool effects that your new cutting edge results were able to extract from an old, useless dataset.
But instead of saying “that’s good pilot data, let’s see if it holds up with a new experiment”, you’re told “you can publish that! Keep this up and maybe you’ll be lucky enough to get a job someday!”