This is a request for continuation of support for a training program in Biostatistics launched in 2005 at the University of Alabama at Birmingham (UAB) to provide support for two pre-doctoral trainees per year for a training period of 4 years. A recent NHLBI RFA-HL-09-009 stated """"""""The current demand for biostatisticians far exceeds the supply, and the gap continues to widen."""""""" Recommendations of two workshops (2001, 2003) held by the National Institutes of Health (NIH) were published as a Training of the next generation of biostatisticians: a call to action in the U.S. (Statistics In Medicine 25(20): 3415-3429. 2006). The workshops examined the need to train more biostatisticians to meet the increasing opportunities in the biomedical research enterprise. The supply of new PhD graduates in biostatistics in the U.S. has been relatively steady for the past two decades while the demand has increased dramatically. These workshops concluded that a renewed effort must be made in the U.S., led in part by the NIH, to add to and expand the existing training programs to increase the supply. The Biostatistics Department at UAB is well poised to help meet the recognized need. Our department has undergone a renaissance in the past 9 years and developed significant strength in: Statistical Genetics;Clinical Trials Design &Analysis;and Design &Analysis of Epidemiologic Studies. We have a large, well-funded, ^highly active department that is evenly split between methodological and applied research. Both our university and department have evidenced strong commitments to training the next generation of biostatisticians through allocation of substantial effort and financial resources to building a vital educational program. The proposed structured training program offers pre-doctoral fellowships to prepare scientists for careers in biostatistics specifically aimed at heart, lung and blood (HLB) research. The program aims to develop independent investigative skills in the development, evaluation, and application of advanced statistical methods. To support this goal, applied experience is provided via co-mentorship by UAB's well established NHLBI-funded investigators.
| Loop, Matthew Shane; McClure, Leslie A; Levitan, Emily B et al. (2018) Fine particulate matter and incident coronary heart disease in the REGARDS cohort. Am Heart J 197:94-102 |
| Merrill, Peter D; Ampah, Steve B; He, Ka et al. (2017) Association between trace elements in the environment and stroke risk: The reasons for geographic and racial differences in stroke (REGARDS) study. J Trace Elem Med Biol 42:45-49 |
| McClure, Leslie A; Loop, Matthew S; Crosson, William et al. (2017) Fine Particulate Matter (PM2.5) and the Risk of Stroke in the REGARDS Cohort. J Stroke Cerebrovasc Dis 26:1739-1744 |
| Balena-Borneman, Jessica; Ambalavanan, Namasivayam; Tiwari, Hemant K et al. (2017) Biomarkers associated with bronchopulmonary dysplasia/mortality in premature infants. Pediatr Res 81:519-525 |
| Loop, Matthew Shane; Howard, George; de Los Campos, Gustavo et al. (2017) Heat Maps of Hypertension, Diabetes Mellitus, and Smoking in the Continental United States. Circ Cardiovasc Qual Outcomes 10: |
| Dionne-Odom, Jodie; Mbah, Rahel; Rembert, Nicole J et al. (2016) Hepatitis B, HIV, and Syphilis Seroprevalence in Pregnant Women and Blood Donors in Cameroon. Infect Dis Obstet Gynecol 2016:4359401 |
| Loop, Matthew Shane; Van Dyke, Melissa K; Chen, Ligong et al. (2016) Comparison of Length of Stay, 30-Day Mortality, and 30-Day Readmission Rates in Medicare Patients With Heart Failure and With Reduced Versus Preserved Ejection Fraction. Am J Cardiol 118:79-85 |
| George, Brandon J; Beasley, T Mark; Brown, Andrew W et al. (2016) Common scientific and statistical errors in obesity research. Obesity (Silver Spring) 24:781-90 |
| Mehta, Tapan; Pajewski, Nicholas M; Keith, Scott W et al. (2016) Role of a plausible nuisance contributor in the declining obesity-mortality risks over time. Exp Gerontol 86:14-21 |
| George, Brandon; Denney Jr, Thomas; Gupta, Himanshu et al. (2016) APPLYING A SPATIOTEMPORAL MODEL FOR LONGITUDINAL CARDIAC IMAGING DATA. Ann Appl Stat 10:527-548 |
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