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A Bayesian dose-finding design for outcomes evaluated with uncertainty.
Schipper, Matthew J; Yuan, Ying; Taylor, Jeremy Mg; Ten Haken, Randall K; Tsien, Christina; Lawrence, Theodore S.
Affiliation
  • Schipper MJ; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Yuan Y; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
  • Taylor JM; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Ten Haken RK; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Tsien C; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
  • Lawrence TS; Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Clin Trials ; 18(3): 279-285, 2021 06.
Article in En | MEDLINE | ID: mdl-33884907
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Research Design / Bayes Theorem / Dose-Response Relationship, Drug / Drug-Related Side Effects and Adverse Reactions Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Clin Trials Journal subject: MEDICINA / TERAPEUTICA Year: 2021 Type: Article Affiliation country: United States
Fulltext
Print
XML
PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Research Design / Bayes Theorem / Dose-Response Relationship, Drug / Drug-Related Side Effects and Adverse Reactions Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Clin Trials Journal subject: MEDICINA / TERAPEUTICA Year: 2021 Type: Article Affiliation country: United States