Anzeige
Erschienen in:
2017 | OriginalPaper | Buchkapitel
On Fishing for Significance and Statistician’s Degree of Freedom in the Era of Big Molecular Data
verfasst von : Anne-Laure Boulesteix, Roman Hornung, Willi Sauerbrei
Erschienen in: Berechenbarkeit der Welt?
Verlag: Springer Fachmedien Wiesbaden
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
There are usually plenty of conceivable approaches to statistically analyze data that both make sense from a substantive point of view and are defensible from a theoretical perspective. The data analyst has to make a lot of choices, a problem sometimes referred to as “researcher’s degree of freedom”. This leaves much room for (conscious or subconscious) fishing for significance: the researcher (data analyst) sometimes applies several analysis approaches successively and reports only the results that seem in some sense more satisfactory, for example in terms of statistical significance. This may lead to apparently interesting but false research findings that fail to get validated in independent studies. In this essay we describe and illustrate these problems and discuss possible strategies to (partially) address them such as validation, increased development of guidance documents, and publication of negative research findings, analysis plans, data and code.