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.
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