Misalignment between research hypotheses and statistical hypotheses: A threat to evidence-based medicine?

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Insa Lawler, Assistant Professor (Creator)
The University of North Carolina at Greensboro (UNCG )
Web Site: http://library.uncg.edu/

Abstract: Evidence-based medicine frequently uses statistical hypothesis testing. In this paradigm, data can only disconfirm a research hypothesis’ competitors: One tests the negation of a statistical hypothesis that is supposed to correspond to the research hypothesis. In practice, these hypotheses are often misaligned. For instance, directional research hypotheses are often paired with non-directional statistical hypotheses. Prima facie, one cannot gain proper evidence for one’s research hypothesis employing a misaligned statistical hypothesis. This paper sheds lights on the nature of and the reasons for such misalignments and it provides a thorough analysis of whether they pose a threat to evidence-based medicine. The upshots are that the misalignments are often hidden for clinicians and that although some cases of misalignments can be partially counterbalanced, the overall threat is non-negligible. The counterbalances either lead to methodological inadequacy (in addition to the misalignment), loss of statistical power, or involve a (potential) lack of information that could be crucial for decision making. This result casts doubt on various findings of medical studies in addition to issues associated with under-powered studies or the replication crisis.

Additional Information

Topoi. DOI: 10.1007/s11245-019-09667-0
Language: English
Date: 2019
Research hypotheses, Statistical hypothesis testing, Null hypotheses, Evidence-based medicine, Clinical decision making

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