The headline of this post is the title of a fascinating new paper in the Journal of Management suggesting that if the road to publication is paved with good intentions, it may also be paved with bad scientific practice.
Ernest Hugh O’Boyle and colleagues tracked 142 management and applied psychology PhD theses to publication, and looked for various questionable research practices — they abbreviate those “QRPs” — such as deleting or adding data after hypothesis tests, selectively adding or deleting variables, and adding or deleting hypotheses themselves.
Our primary finding is that from dissertation to journal article, the ratio of supported to unsupported hypotheses more than doubled (0.82 to 1.00 versus 1.94 to 1.00). The rise in predictive accuracy resulted from the dropping of statistically nonsignificant hypotheses, the addition of statistically significant hypotheses, the reversing of predicted direction of hypotheses, and alterations to data. We conclude with recommendations to help mitigate the problem of an unrepresentative literature that we label the “Chrysalis Effect.”
Specifically, they found:
Of the 1,978 hypotheses contained in the dissertations (i.e., dropped and common hypotheses), 889 (44.9%) were statistically significant.1 That less than half of the hypotheses contained in a dissertation are supported with statistical significance is troubling, but more troubling is that 645 of the 978 (65.9%) hypotheses published in the journal articles (i.e., added and common hypotheses) were statistically significant. This is a 21.0% inflation of statistically significant results and corresponds to more than a doubling of the ratio of supported to unsupported hypotheses from 0.82:1 in the dissertations to 1.94:1 in the journal articles. To our knowledge, this is the first direct documentation of the prevalence, severity, and effect of QRPs in management research, and on the basis of these findings, we conclude that the published literature, at least as it relates to those early research efforts by junior faculty, is overstating its predictive accuracy by a substantial margin. Thus, we find evidence to support a Chrysalis Effect in management and applied psychology.
The authors are not naive:
Despite increased awareness of what QRPs are and the damage they cause (e.g., Bedeian et al., 2010; Martinson, Anderson, & De Vries, 2005), QRPs persist. We contend that this is because as a field, we reward QRPs, and we are embedded within a culture that reduces the likelihood of their detection. As such, QRP reductions are unlikely to occur by placing the onus of best practices on the individual researcher. Asking researchers to forego immediate, extrinsic rewards in order to serve the higher ideals of fair play and professional ethics is a noble request, but one that is unlikely to manifest into real change.
They offer a few solutions, including an “honor code” in which all of the authors — not just the corresponding author — “affirm that they did not engage in any of the specific QRPs discussed here” when they submit a manuscript.
The authors also sound a warning:
If we cannot self-police by establishing and enforcing best practices, then those external stakeholders that provide funding (e.g., state governments, federal grant agencies, private individuals and organizations) may reduce or withdraw their support.
You can hear O’Boyle discuss the findings in this podcast.
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