The principal objective of the Biostatistics Core will be to provide project investigators a centralized resource for biostatistics expertise. Statistical issues will be addressed at all levels of investigation: from the design of clinical trials and laboratory experiments, to the maintenance of data quality;and from conclusions based on formal hypothesis testing, to important leads discovered by thorough data exploration. In support of this objective, the specific aims of the Core include: 1. Design: collaborate with project investigators in the design of clinical studies and laboratory experiments, formulation of unambiguous hypotheses and hypothesis testing strategies, and development and validation of predictive models. Analysis: provide support with: formal hypothesis tests in clinical and experimental data that ensure strong conclusions;statistical modeling and sensitivity analyses of prospective and retrospective studies;integrated analyses for discovery, training, and validation of predictive models;exploratory analyses that lead to further studies and experiments;and visual displays of data that clarify conclusions and uncover leads. Oversight and Infrastructure: provide oversight for the clinical trials, including design adherence and interim analyses, web based randomization, and data coordination services. Data Quality Assurance: manage data and coordinate services with the Integrated Clinicopathology and Biorepository Core to ensure high quality, security and investigator accessibility for all clinical and experimental data. Methods Research: Investigate new methodologies to directly address difficult data or design problems. Pilot projects: provide design and data analytic support for pilot projects.
The Biostatistics Core will provide critical support for planning and design of experiments and studies, statistical analyses and display of data, and data management and integrity. This support is designed to ensure that studies yield reliable conclusions, resources are efficiently used, and exploratory analyses uncover important leads.
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|Wang, Yanqiang; He, Huiling; Liyanarachchi, Sandya et al. (2018) The role of SMAD3 in the genetic predisposition to papillary thyroid carcinoma. Genet Med 20:927-935|
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