Von P-Hacking, Clickbait-Bullshit und Schoko-Diäten


Schöner Scoop von Diana Löbl und Peter Onneken, die Bullshit an die Clickbait-Industrie verkauft haben. Ist so ein bisschen wie (schon wieder) Trust me, I'm lying, nur mit Science. (via Stefan Niggemeier)

scoooWirklich interessant wird das dann, wenn man die Story eines beteiligten Wissenschaftlers durchliest: „Think of the measurements as lottery tickets. Each one has a small chance of paying off in the form of a 'significant' result that we can spin a story around and sell to the media. The more tickets you buy, the more likely you are to win. We didn’t know exactly what would pan out—the headline could have been that chocolate improves sleep or lowers blood pressure—but we knew our chances of getting at least one “statistically significant” result were pretty good.“

Und wenn man dann ganz tief ins P-Hacking-Rabbithole runterklettern will, hier eine Liste mit hunderten Bullshit-Formulierungen für Schokodiät-Clickbaitscience-Statistiken: Still Not Significant.

[If] your p-value remains stubbornly higher than 0.05, you should call it ‘non-significant’ and write it up as such. The problem for many authors is that this just isn’t the answer they were looking for: publishing so-called ‘negative results’ is harder than ‘positive results’.

The solution is to apply the time-honoured tactic of circumlocution to disguise the non-significant result as something more interesting. The following list is culled from peer-reviewed journal articles in which (a) the authors set themselves the threshold of 0.05 for significance, (b) failed to achieve that threshold value for p and (c) described it in such a way as to make it seem more interesting.

Hier ein paar Favorites:

a barely detectable statistically significant difference (p=0.073)
a considerable trend toward significance (p=0.069)
a nonsignificant trend toward significance (p=0.1)
approaches but fails to achieve a customary level of statistical significance (p=0.154)
barely fails to attain statistical significance at conventional levels (p<0.10 bordered on but was not less than the accepted level of significance (p>0.05)
fell just short of the traditional definition of statistical significance (p=0.051)
not exactly significant (p=0.052)
not that significant (p=0.08)