BIOSTATISTICAL CORE

生物统计学核心（BC）为耶鲁大学OIAC提供最先进的生物统计学专业知识。具体 核心的职能是确保多因素老年健康研究的适当设计和分析 发展和应用新的统计方法，并发展和建立教育和 培训项目。BC将为耶鲁大学OAIC提供以下服务： 在准备OAIC赠款时，确保使用适当的研究设计，请咨询初级和 研究设计和分析问题的高级研究员，作为设计和统计方面的资源 问题，进行统计分析，与研究者合作准备手稿，提供 初级临床研究者、生物统计学家和 流行病学家，并开发或应用新的方法。BC工作人员拥有广泛的统计数据， 专业知识，使他们能够为耶鲁OAIC的使命做出贡献。这些专业知识包括： 实验设计（随机临床试验，流行病学研究，可靠性研究，聚类设计， 和多因素老年健康状况的多成分干预措施），回归和纵向 方法（多元线性、二项和逻辑回归;分层线性模型;广义估计 方程;以及广义线性和非线性混合模型）、生存模型（比例风险 单一和重复事件模型，多态模型），插补，贝叶斯方法，时空 建模、随机模型和计算生物学。建筑小组委员会建议在 新兴的计算生物学领域，其总体目标是建立一个合作团队， 研究人员开发新的系统生物学方法来研究衰老。核心的未来方向是 建立老年生物统计学项目，培养下一代老年生物统计学家， research.

The Biostatistics Core (BC) provides state of the art biostatistical expertise for the Yale OIAC. The specific functions of the core are to ensure the proper design and analysis of studies of multifactorial geriatric health conditions, to develop and apply new statistical methodology, and to develop and institute education and training programs. The BC will provide the following services to the Yale OAIC: collaborate with investigators in the preparation of OAIC grants to ensure proper research designs are being used, consult with junior and senior investigators about study design and analysis issues, serve as a resource about design and statistical issues, perform statistical analyses, collaborate with investigators on manuscript preparation, provide mentorship and education and training programs for junior clinical investigators, biostatisticians and epidemiologists, and develop or apply new methodology. The BC staff has a broad range of statistical expertise that will enable them to contribute to the mission of the Yale OAIC. This expertise includes: experimental design (randomized clinical trials, epidemiological studies, reliability studies, clustered designs, and multi-component interventions for multifactorial geriatric health conditions), regression and longitudinal methods (multiple linear, binomial and logistic regression; hierarchical linear models; generalized estimating equations; and generalized linear and non linear mixed models), survival models (proportional hazards models with single and recurrent events, multistate models), imputation, Bayesian methods, spatio-temporal modeling, stochastic models and computational biology. The BC is proposing a development project in the emerging field of computational biology with the overarching aim to establish a collaborative team of researchers to develop new systems biology approaches to aging research. A future direction of the Core is to establish a program for gerontologic biostatistics to train the next generation of biostatisticians in geriatric research.