One consequence of the on-going "replication" crisis in the social (and, increasingly, hard) sciences is a spike in the salience of the term "p-Hacking." The term "p-Hacking," as defined by Robert MacCoun (Stanford) in his recent essay, p-Hacking: A Strategic Analysis, “joins a growing taxonomy for describing the myriad ways in which ‘cold cognitive’ and ‘hot motivational’ biases can creep into the interpretation and use of research findings.” In his brief essay MacCoun dives deeply into the issue and proposes “four different models of p-hacking behavior and examining what kinds of aggregate patterns they might be expected to produce.” The abstract follows.
"The phenomenon of p-hacking occurs when researchers engage in questionable practices that enable them to report findings as being statistically significant. I offer four models of p-hacking behavior – unconditional, strategic, greedy, and restrained – and explore the implications of each model. I then discuss the implications of recent reforms (routine replication, pre-registration, and blinded data analysis) with respect to these models."
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