BIOSTATISTICAL SUPPORT UNIT

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BIOSTATISTICAL SUPPORT UNIT The Biostatistical Support Unit (BSU) is one of the multi-user core research facilities currently supported by the National Institutes of Health-RCMI Center for Environmental Health at Jackson State University (JSU). In recent years, the BSU has significantly contributed to the success of the RCMI Program at JSU, by providing RCMI investigators with capabilities in biostatistics, applied environmental statistics, statistical computing, and database and information management. The impact of the BSU on the RCMI Program is evidenced by thirty two peer-reviewed publications and seven doctoral research dissertations over the past 5 years. Also, the BSU currently supports fourteen research projects conducted by faculty and students in the College of Science, Engineering and Technology. This Unit has also worked closely with the Pis of the four pilot projects that are included in the RCMI grant renewal application; by ensuring that the study designs are adequate, including the development of study hypotheses, the identification of research end-points, the determination of experimental groups, control groups and sample sizes, and the use of appropriate statistical tests. It is also anticipated that the BSU will provide advice in data collection, analysis and interpretation, as well as in data management and publication. The overarching goals of the BSU are to: a) strengthen its biomedical research infrastructure; b) provide all aspects of bio-statistical services to RCMI investigators; and c) foster interdisciplinary research collaborations among these investigators and their peers at JSU and other institutions of higher learning. Therefore, the specific aims of the BSU are: 1) To enhance the existing biostatistics-related infrastructure by acquiring new hardware and software; 2) To provide expertise for the planning, conduct, analysis and reporting of experiments on health effects of environmental compounds, experiments on therapeutic properties of anti-cancer drugs, clinical trials, epidemiologic and population based studies, and ecological studies; 3) To provide advice for the efficient and accurate database design and management of experimental, clinical, epidemiology, and/or ecologic research data; 4) To provide expertise for scientific computing for data analysis and scientific graphics; 5) To train RCMI investigators and students in the areas of study design, data collection, computerization, and statistical methods for laboratory, clinical, population-based, and/or ecological studies; and 6) To collaborate with the RTRN-Data Technology Coordinating Center leverage resources for a more efficient design of experiments and protocols, and management of data generated from T1 and T2 translational research.