Causal inference for oncology: past developments and current challenges
Abstract: In this paper, we review some important early developments on causal inference in medical statistics and epidemiology that were inspired by questions in oncology. We examine two classical examples from the literature and point to a current area of ongoing methodological development, namely the estimation of optimal adaptive treatment strategies. While causal approaches to analysis have become more routine in oncology research, many exciting challenges and open problems remain, particularly in the context of censored outcomes.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Causal inference for oncology: past developments and current challenges ; volume:19 ; number:2 ; year:2022 ; pages:273-281 ; extent:9
The international journal of biostatistics ; 19, Heft 2 (2022), 273-281 (gesamt 9)
- Creator
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Moodie, Erica E. M.
- DOI
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10.1515/ijb-2022-0056
- URN
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urn:nbn:de:101:1-2023111413163117813746
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:57 AM CEST
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Associated
- Moodie, Erica E. M.
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