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MacDougall, M (2014)

Assessing the Integrity of Clinical Data: When is Statistical Evidence Too Good to be True?

Topoi 33(2), pp. 323–337.

ISSN/ISBN: Not available at this time. DOI: 10.1007/s11245-013-9216-5

Abstract: Evidence, as viewed through the lens of statistical significance, is not always as it appears! In the investigation of clinical research findings arising from statistical analyses, a fundamental initial step for the emerging fraud detective is to retrieve the source data for cross-examination with the study data. Recognizing that source data are not always forthcoming and that, realistically speaking, the investigator may be uninitiated in fraud detection and investigation, this paper will highlight some key methodological procedures for providing a sounder evidence base for withdrawing from a study on grounds of integrity. The promotion of patient safety is paramount. However, there is a broader rationale for disseminating these ideas. This includes empowering researchers to optimize their personal integrity, make informed choices regarding membership of future research collaborations and successfully voice their concerns to journal editors, particularly where a conflict of interests can render such dialogues particularly difficult. Recommendations will be supported by topical case studies and practical steps involving data exploration, testing of baseline data and application of Benford’s Law. While this paper has a clinical focus, the advice provided is transferrable to a wide range of multidisciplinary research settings outside of Medicine.

@Article{, author="MacDougall, Margaret", title="Assessing the Integrity of Clinical Data: When is Statistical Evidence Too Good to be True?", journal="Topoi", year="2014", month="Oct", day="01", volume="33", number="2", pages="323--337", issn="1572-8749", doi="10.1007/s11245-013-9216-5", url="" }

Reference Type: Journal Article

Subject Area(s): Medical Sciences, Psychology, Statistics