Abstract
In an attempt to stem the practice of reporting impressive-looking findings based on data dredging and multiple testing, the American Statistical Association's (ASA) 2016 guide to interpreting p values (Wasserstein & Lazar) warns that engaging in such practices “renders the reported p-values essentially uninterpretable” (pp. 131-132). Yet some argue that the ASA statement actually frees researchers from culpability for failing to report or adjust for data dredging and multiple testing. We illustrate the puzzle by means of a case appealed to the Supreme Court of the United States: that of Scott Harkonen. In 2009, Harkonen was found guilty of issuing a misleading press report on results of a drug advanced by the company of which he was CEO. Downplaying the high p value on the primary endpoint (and 10 secondary points), he reported statistically significant drug benefits had been shown, without mentioning this referred only to a subgroup he identified from ransacking the unblinded data. Nevertheless, Harkonen and his defenders argued that “the conclusions from the ASA Principles are the opposite of the government's conclusion that his construal of the data was misleading (Harkonen v. United States, 2018, p. 16). On the face of it, his defenders are selectively reporting on the ASA guide, leaving out its objections to data dredging. However, the ASA guide also points to alternative accounts to which some researchers turn to avoid problems of data dredging and multiple testing. Since some of these accounts give a green light to Harkonen’s construal, a case might be made that the guide, inadvertently or not, frees him from culpability.Keywords: statistical significance, p values, data dredging, multiple testing, ASA guide to p values, selective reporting
Highlights
The biggest source of handwringing about statistical inference boils down to the fact it has become very easy to infer claims that have not been subjected to stringent tests
What makes the case intriguing is not its offering yet another case of p-hacking, nor that it has found its way more than once to the Supreme Court. It is because in 2018, Harkonen and his defenders argued that the ASA guide provides “compelling new evidence that the scientific theory upon which petitioner’s conviction was based [that of statistical significance testing] is demonstrably false” (Goodman, 2018, p. 3)
It would not be correct to claim p values cannot be interpreted without knowing of the data dredging, if their influence on error probabilities did not affect the import of the data
Summary
The biggest source of handwringing about statistical inference boils down to the fact it has become very easy to infer claims that have not been subjected to stringent tests. What makes the case intriguing is not its offering yet another case of p-hacking, nor that it has found its way more than once to the Supreme Court Rather, it is because in 2018, Harkonen and his defenders argued that the ASA guide provides “compelling new evidence that the scientific theory upon which petitioner’s conviction was based [that of statistical significance testing] is demonstrably false” It is because in 2018, Harkonen and his defenders argued that the ASA guide provides “compelling new evidence that the scientific theory upon which petitioner’s conviction was based [that of statistical significance testing] is demonstrably false” Whether they exonerate Harkonen’s defenders is for you, the jury, to decide
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