数据造假新手段“P值黑客”

如今，在科学研究中，出现了比学术欺诈更令人担忧发指的行为——P值黑客(P-hacking)。

P-hacking refers to the practice of manipulating scientific data so that the results appear to be statistically significant.

“P值黑客”是指操作科学数据，从而使结果看上去具有统计学意义的行为。

这个词最早由宾夕法尼亚大学的西蒙松教授提出，一起来看看他是怎么说的：

Professor Uri Simonsohn of UPenn discussed what he refers to as "p-hacking." P-hacking is the idea that if researchers are engaging in questionable analysis practices, then they should have a disproportionate number of findings at or close to the p .05 threshold for statistical significance, and that this can be relatively easy to detect.

宾夕法尼亚大学西蒙松教授谈到他所指的P值黑客。P值黑客是指如果研究人员采用的分析方法可疑，那么他们应当有一个不成比例的P值数据结果等于或接近p0.05这个统计学意义阀值，而这也相对很容易被发现。

虽然直译为“P值黑客”，但从定义上看，该词有“数据造假”的意思，这点可以从《大西洋月刊》上的文章《自我修正的科学之谜》(The Myth of Self-Correcting Science)中的解释得到佐证：

Almost more alarming than the few individuals committing academic fraud are the high percentage of researchers who admitted to more common questionable research practices, like post-hoc theorizing and data-fishing (sometimes referred to as p-hacking), in a recent study led by Leslie John.

近期由莱斯利·约翰主导的研究指出，比少数人的学术欺诈行为更令人担忧的是，有很高比例的研究人员承认他们的做法更普遍更不靠谱，如事后推理和数据造假(有时指P值黑客)。