Issues with data and analyses: Errors, underlying themes, and potential solutions
There is a sense of irony that our paper about issues with data and how to prevent and correct errors came out just after our letter to the editor attempting to correct a misanalyzed cluster randomized trial was dismissed by the authors. Perhaps had we been able to share our article describing these errors and a variety of ways to prevent and correct them, the response would have been different.
Given our experiences with other attempts to correct the literature, though, that is doubtful.
In our letter, we lay out that the authors prespecified the appropriate analysis, ignored the correct analysis for certain comparisons in their paper, and then used the misanalyzed results as the focus for their press-releases. Although we offered to work with the authors in private because we believe collaboration can be more constructive than letters back and forth, the authors turned us down. In turn, their reply to our letter did not acknowledge their error. In fact, they doubled down by claiming that because others made the mistake in the past it was okay. Ted Kyle with ConscienHealth describes it more.
Our PNAS article describes challenges such as these and others we faced when trying to identify and correct the literature.
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