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[Introduction of landmarking approach and its application in dynamic prediction].
Zhou, J J; Wang, S F.
Afiliação
  • Zhou JJ; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
  • Wang SF; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(1): 112-117, 2022 Jan 10.
Article em Zh | MEDLINE | ID: mdl-35130661
ABSTRACT
Conventional prediction model, as a static prediction model, can be only used to predict the probability of the occurrence of an event during the observation period using the information available at baseline survey. However, based on current clinical demands, dynamic prediction, which obtains prediction probabilities for both baseline survey and later time points given the history of the events and covariates up to that time, is gaining a growing attention. As a dynamic prediction model, the landmarking approach is simple, easy to use, computationally efficient and has a comparable performance of joint modeling, which makes it to be widely used in recent researches. Because of its limited application in China, this paper makes a brief introduction of its ideas and basic application to further promote its applications in clinical dynamic prediction.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Probabilidade Idioma: Zh Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Probabilidade Idioma: Zh Ano de publicação: 2022 Tipo de documento: Article