Flexible statistical models for dynamic prediction in survival analysis with time-varying prognostic factors

用于随时间变化的预后因素进行生存分析的动态预测的灵活统计模型

• 批准号: RGPIN-2017-04339
• 负责人: Abrahamowicz, Michal
• 金额: $ 2.7万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635910
• 关键词: Flexible; statistical; models; dynamic; prediction

The long-term objective of my research is to develop new, flexible statistical methods that will enhance the scientific validity of clinical studies on the occurrence, progression, treatment and outcomes of many diseases. Studies of human health face many conceptual and methodological challenges, and the mission of biostatistics is to elaborate sophisticated methods to address these challenges.

我的研究的长期目标是开发新的，灵活的统计方法，这将提高对许多疾病的发生，进展，治疗和结果的临床研究的科学有效性。人类健康的研究面临着许多概念和方法上的挑战，生物统计学的使命是制定复杂的方法来应对这些挑战。