The Statistical Core supports the Projects by providing the data management and analytical services described in the Aims below. Broadly, our goals are to facilitate and ensure accuracy, cost efficiency and appropriate interpretation in the achievement of the scientific aims from each Project. Statistical Core leader Dr. Amalia Magaret has 9 years of experience planning and analyzing studies of herperviruses as well as designing derivative statistical methodology. Data manager Stacy Selke developed the data management procedures which have facilitated collection, quality assurance and sharing of laboratory and clinical data between POI Projects and Cores for 25 years. In the recent cycle. Dr. Joshua Schiffer has developed mathematical models deepening our understanding of the mechanisms influencing viral shedding and the role of the host immune response in containing the virus in the mucosa. Our team is integral to the scientific aims of this POI through our familiarity with the large store of data amassed by our clinic, our established relationships, and our collective experience in HSV research.
Our aims are:
Aim 1 : Consult in the design of experimental methods, including sample size computation, and the conceptualization of Viral dynamics studies.
Aim 2 : Coordinate data management, overseeing data collection procedures, laboratory sample management, results handling and integration of diverse data sources.
Aim 3 : Perform appropriate statistical analyses and modeling, contributing to the interpretation and reporting of results.
Aim 4 : Design novel dynamical mathematical models and other statistical methodologies as needed, optimizing our analytic approach.
The Statistical Core assists all Projects by helping the investigators plan, carry out and analyze their findings using appropriate methods. Our contribution helps ensure that the Specific Aims of each Project include the correct number of participants and samples, and that the subsequent scientific evidence is represented, interpreted and disseminated accurately
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