Biostatistics and Data Integration

有效和知识渊博的生物统计学支持对于正确设计和解释 生物医学科学方面的研究。生物统计核心的主要目标将是提供 甲状腺癌研究人员是统计专业知识的集中资源.统计问题将是 在各个层面的调查中得到解决：从实验设计到数据源整合 和维护数据质量，以及从建模描述到以下所需的推论语句 精准传播。为支持这一目标，生物统计核心的具体目标包括： 1.与项目调查人员合作，制定假设和进行假设检验 所有小鼠和细胞系实验的策略，以及在预后/诊断、连锁、 和微阵列研究。 2.对项目调查员产生的数据进行和指导统计分析，包括： 描述性汇总统计、误差建模、实验数据推断和决策， 连锁和微阵列研究的分析和数据准备，以及预后/诊断方程式 建模和精度估计。 3.为了确保与以下相关的统计原则：建立滋扰或阻塞效应的模型，最小化 通过对多个比较和多个测量进行校正来推断错误(类型I和类型II错误)， 在所有研究中都采用了适当的随机化条件和减小测量误差的方法。 4.提供数据传输、管理和集成服务，确保高度完整性、安全性和 调查员可访问性。 5.与核心A(临床数据)和核心B(鼠标)董事合作，确保上述目标 原则用于从全面和公正的研究中获得有效和可靠的数据 设计。 6.必要时协调较新统计方法的开发和调查，以 直接支持正在进行的研究。

Efficient and knowledgeable biostatistical support is crucial to the proper design and interpretation of research in the biomedical sciences. The principal objective of the Biostatistics Core will be to provide the Thyroid cancer investigators a centralized resource for statistical expertise. Statistical issues will be addressed at all levels of investigation: from the design of experiments, to the integration of data sources and maintenance of data quality, and from descriptions of modeling to inferential statements required for accurate dissemination. In support of this objective, the specific aims of the Biostatistics Core include: 1. To collaborate with project investigators in the formulation of hypotheses and hypotheses testing strategies for all mouse and cell line experiments, and in the design of prognostic/diagnostic, linkage, and micro-array studies. 2. To conduct and direct the statistical analysis of data generated by project investigators including: descriptive summary statistics, error modeling, experimental data inference and decision making, analysis and data preparation for linkage and microarray studies, and prognostic/diagnostic equation modeling and accuracy estimation. 3. To ensure that statistical principles associated with: modeling nuisance or block effects, minimizing inference errors (Type I and II error) by correcting for multiple comparisons and multiple measures, randomizing conditions properly, and decreasing measurement error are employed in all studies. 4. Provide data transfer, management, and integration services that ensure high integrity, security and investigator accessibility. 5. To collaborate with Core A (Clinical Data) and Core B (Mouse) directors to ensure the above principles are used in obtaining valid and reliable data from fully powered and unbiased study designs. 6. To coordinate the development and investigation of newer statistical methodologies, when needed, to directly support ongoing research.