Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods ; volume:24 ; number:1 ; day:23 ; month:7 ; year:2024 ; pages:1-9 ; date:12.2024
BMC medical research methodology ; 24, Heft 1 (23.7.2024), 1-9, 12.2024
- Klassifikation
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Wirtschaft
- Urheber
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Xu, Edward
Vanghelof, Joseph
Wang, Yiyang
Patel, Anisha
Furst, Jacob
Raicu, Daniela Stan
Neumann, Johannes Tobias
Wolfe, Rory
Gao, Caroline X.
McNeil, John J.
Shah, Raj C.
Tchoua, Roselyne
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1186/s12874-024-02265-8
- URN
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urn:nbn:de:101:1-2411132104274.617443389863
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:21 MESZ
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Beteiligte
- Xu, Edward
- Vanghelof, Joseph
- Wang, Yiyang
- Patel, Anisha
- Furst, Jacob
- Raicu, Daniela Stan
- Neumann, Johannes Tobias
- Wolfe, Rory
- Gao, Caroline X.
- McNeil, John J.
- Shah, Raj C.
- Tchoua, Roselyne
- SpringerLink (Online service)
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