BIOSTATISTICAL CORE

生物统计核心(BC)为耶鲁OIAC提供最先进的生物统计专业知识。具体的 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 培训计划。BC将向耶鲁OAIC提供以下服务：与调查人员合作 在准备OAIC补助金以确保使用适当的研究设计时，咨询初级和 关于研究设计和分析问题的高级调查人员，作为关于设计和统计的资源 问题，进行统计分析，与调查人员合作准备稿件，提供 为初级临床研究人员、生物统计学家和 流行病学家，并开发或应用新的方法。BC的工作人员有广泛的统计数据 将使他们能够为耶鲁OAIC的使命做出贡献的专业知识。这方面的专业知识包括： 实验设计(随机临床试验、流行病学研究、可靠性研究、分组设计、 和多因素老年健康状况的多成分干预)、回归和纵向 方法(多元线性回归、二项回归和Logistic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 具有单次和重复事件的模型、多状态模型)、归因、贝叶斯方法、时空 建模、随机模型和计算生物学。不列颠哥伦比亚省正在提出一个开发项目， 计算生物学的新兴领域，其首要目标是建立一个 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课程，培养下一代老年医学生物统计学人才 研究。

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.