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...
Gespeichert in:
| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
21 February 2025
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| 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 |
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| 520 | |a 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. | ||
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| 650 | 4 | |a Sample representativeness | |
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