KMstability: R tools to report the stability and precision of Kaplan-Meier estimates as well as measures of follow-up in time-to-event studies
In order to appropriately report time-to-event analyses by means of Kaplan-Meier estimates, its precision and stability should be described. The precision is often reported by confidence intervals. For reporting the stability, various measures of the follow-up time distribution are used. However, th...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
May 2024
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| In: |
SoftwareX
Year: 2024, Jahrgang: 26, Pages: 1-6 |
| ISSN: | 2352-7110 |
| DOI: | 10.1016/j.softx.2024.101650 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.softx.2024.101650 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2352711024000219 
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| Verfasserangaben: | Stella Erdmann, Rebecca Betensky |
| Zusammenfassung: | In order to appropriately report time-to-event analyses by means of Kaplan-Meier estimates, its precision and stability should be described. The precision is often reported by confidence intervals. For reporting the stability, various measures of the follow-up time distribution are used. However, these do not provide the intended insight. Recently, a new stability measure was presented. We have developed the software KMstability for calculation and display of this stability measure, including a user-friendly R shiny application and an open-source R package. The software enables informative reporting of time-to-event analysis. This is essential for reporting time-to-event analyses at interim-analyses of clinical trials and for observational (real-world-data) studies. |
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| Beschreibung: | Online verfügbar: 13. Februar 2024 Gesehen am 14.08.2024 |
| Beschreibung: | Online Resource |
| ISSN: | 2352-7110 |
| DOI: | 10.1016/j.softx.2024.101650 |