SAM: Self-adapting mixture prior to dynamically borrow information from historical data in clinical trials.

Yang, Peng; Zhao, Yuansong; Nie, Lei; Vallejo, Jonathon; Yuan, Ying

Yang, Peng; Zhao, Yuansong; Nie, Lei; Vallejo, Jonathon; Yuan, Ying.

Afiliação

Yang P; Department of Statistics, Rice University, Houston, Texas, USA.
Zhao Y; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Nie L; Department of Biostatistics, The University of Texas Health Science Center, Houston, Texas, USA.
Vallejo J; Center for Drug Evaluation and Research, Food and Drug Administration (FDA), Silver Spring, Maryland, USA.
Yuan Y; Center for Drug Evaluation and Research, Food and Drug Administration (FDA), Silver Spring, Maryland, USA.

Biometrics ; 79(4): 2857-2868, 2023 12.

Article em En | MEDLINE | ID: mdl-37721513

Assuntos

Modelos Estatísticos; Projetos de Pesquisa; Teorema de Bayes; Tamanho da Amostra; Funções Verossimilhança; Calibragem

Palavras-chave

adaptive design; dynamic information borrowing; historical data; mixture distribution; rare diseases; real-world data

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / Modelos Estatísticos Idioma: En Revista: Biometrics Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

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