Biostatistics Core

核心C：生物统计核心的工作人员将负责向 这一方案的研究。生物统计核心由蒂莫西·D·约翰逊博士监督 密歇根大学公共卫生学院生物统计学系。核心提供了 协助设计、分析和解释该计划的临床前和临床试验 项目。核心人员将与项目调查人员互动，以确保适当的设计和 采用了分析的方法。设计问题涉及剂量选择、随机化、测量时间 和样本量。对于数据分析，核心将确保使用有效的方法。标准 将采用图表、分组比较和相关分析的方法进行初步调查 实验数据。混合模型方法将被用来在实验中有效利用数据，包括 反复采取措施。核心人员在动物和临床的设计和分析方面都有经验。 数据。这将确保所有从成像测量、肿瘤组织学、净细胞杀伤 将有效地收集与治疗和患者结果相关的信息并进行适当的分析。 相关性(请参阅说明)： 总体而言，这项研究工作将为使用最先进的成像配准提供理论基础 临床癌症患者管理的技术和定量成像技术。

CORE C: The staff of the Biostatistics Core will be responsible for providing statistical support to the research of this program. The Biostatistics Core is under the supervision of Dr. Timothy D. Johnson of the Biostatistics Department at the University of Michigan, School of Public Health. The core provides assistance in the design, analysis and interpretation of preclinical and clinical experiments of the program project. Core personnel will interact with project investigators to ensure that appropriate designs and methods of analysis are used. Design issues involve dose selection, randomization, time of measurements and sample size. For analysis of data, the core will ensure that efficient methods are used. Standard graphical, group comparison and correlation methods of analysis will be used for initial investigation of the experimental data. Mixed models methods will be used for efficient use of data in experiments involving repeated measures. Core personnel are experienced in the design and analysis of both animal and clinical data. This will ensure that all data obtained from imaging measurements, tumor histology, net cell kill associated with therapy and patient outcome will be collected efficiently and analyzed appropriately. RELEVANCE (See instructions): Overall, this research effort will provide the rationale for the use of state-of-the-art imaging registration techniques and quantitative imaging techniques for the management of clinical cancer patients.