Assessing the representativeness of large medical data using population stability index

Understanding sample representativeness is key to interpreting findings from epidemiological research and applying these findings to broader populations. Though techniques for assessing sample representativeness are available, they rely on access to raw data detailing the population of interest whic...

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Hauptverfasser: Lu, Sheng-Chieh (VerfasserIn) , Song, Wenye (VerfasserIn) , Pfob, André (VerfasserIn) , Gibbons, Chris (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 21 February 2025
In: BMC medical research methodology
Year: 2025, Jahrgang: 25, Pages: 1-8
ISSN:1471-2288
DOI:10.1186/s12874-025-02474-9
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12874-025-02474-9
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Verfasserangaben:Sheng-Chieh Lu, Wenye Song, Andre Pfob and Chris Gibbons
Beschreibung
Zusammenfassung:Understanding sample representativeness is key to interpreting findings from epidemiological research and applying these findings to broader populations. Though techniques for assessing sample representativeness are available, they rely on access to raw data detailing the population of interest which are often not readily available and may not be suitable for comparing large datasets. In reality, population-based data are often only available in an aggregated format. In this study, we aimed to examine the capability of population stability index (PSI), a popular metric to assess data drift for artificial intelligence studies, in detecting sample differences using population-based data.
Beschreibung:Gesehen am 01.10.2025
Beschreibung:Online Resource
ISSN:1471-2288
DOI:10.1186/s12874-025-02474-9