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.

National Institute of Health (NIH)
Institutional National Research Service Award (T32)
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NHLBI Institutional Training Mechanism Review Committee (NITM)
Program Officer
Silsbee, Lorraine M
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University of Alabama Birmingham
Biostatistics & Other Math Sci
Schools of Public Health
United States
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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
Dawson, J A; Kaiser, K A; Affuso, O et al. (2016) Rigorous control conditions diminish treatment effects in weight loss-randomized controlled trials. Int J Obes (Lond) 40:895-8
Yang, Celeste; Bartolucci, Alfred A; Cui, Xiangqin (2015) Multigroup Equivalence Analysis for High-Dimensional Expression Data. Cancer Inform 14:253-63
George, Brandon; Aban, Inmaculada (2015) Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data. Stat Med 34:145-61
Li, Peng; Redden, David T (2015) Small sample performance of bias-corrected sandwich estimators for cluster-randomized trials with binary outcomes. Stat Med 34:281-96
Li, Peng; Redden, David T (2015) Comparing denominator degrees of freedom approximations for the generalized linear mixed model in analyzing binary outcome in small sample cluster-randomized trials. BMC Med Res Methodol 15:38
Dudenbostel, Tanja; Acelajado, Maria C; Pisoni, Roberto et al. (2015) Refractory Hypertension: Evidence of Heightened Sympathetic Activity as a Cause of Antihypertensive Treatment Failure. Hypertension 66:126-33
Aban, Inmaculada B; George, Brandon (2015) Statistical considerations for preclinical studies. Exp Neurol 270:82-7
Affuso, O; Kaiser, K A; Carson, T L et al. (2014) Association of run-in periods with weight loss in obesity randomized controlled trials. Obes Rev 15:68-73
Kaiser, Kathryn A; Affuso, Olivia; Desmond, Renee et al. (2014) Baseline participant characteristics and risk for dropout from ten obesity randomized controlled trials: a pooled analysis of individual level data. Front Nutr 1:

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