The University of Washington, Department of Biostatistics, together with faculty from the Departments of Epidemiology, Medicine and Statistics, proposes to train biostatisticians for collaborative work in HIV/AIDS research. This renewal of a very successful training grant would support 4 predoctoral trainees. The PhD program includes coursework in statistical theory, biostatistical methodology, and data analysis, and a statistical consulting practicum. Coursework in the biological sciences related to HIV/AIDS, and an oral examination on a topic in HIV/AIDS biology or medicine, are required. After satisfying these requirements the student proceeds to complete a doctoral dissertation. The research component of the training program will focus on collaboration in ongoing biostatistical methodology research and significant involvement in HIV/AIDS clinical research projects. All trainees are additionally required to attend and contribute to ongoing seminar series that provide collaborative HIV/AIDS research opportunities. Students are enrolled with prior training in mathematics, statistics, or the biological sciences. Program prerequisites include linear algebra, probability, and two years of calculus;promising students with biology majors may be admitted provisionally if they have not satisfied all the mathematical prerequisites.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Institutional National Research Service Award (T32)
Project #
5T32AI007450-20
Application #
8102086
Study Section
Acquired Immunodeficiency Syndrome Research Review Committee (AIDS)
Program Officer
Williams, Carolyn F
Project Start
1992-09-30
Project End
2013-08-31
Budget Start
2011-09-01
Budget End
2013-08-31
Support Year
20
Fiscal Year
2011
Total Cost
$128,925
Indirect Cost
Name
University of Washington
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Odem-Davis, K; Fleming, T R (2015) A simulation study evaluating bio-creep risk in serial non-inferiority clinical trials for preservation of effect. Stat Biopharm Res 7:12-24
Odem-Davis, Katherine; Fleming, Thomas R (2013) Adjusting for unknown bias in non-inferiority clinical trials. Stat Biopharm Res 5:
Fleming, Thomas R; Odem-Davis, Katherine; Rothmann, Mark D et al. (2011) Some essential considerations in the design and conduct of non-inferiority trials. Clin Trials 8:432-9
Renner, Brandon; Strassheim, Derek; Amura, Claudia R et al. (2010) B cell subsets contribute to renal injury and renal protection after ischemia/reperfusion. J Immunol 185:4393-400
Moskowitz, Chaya S; Pepe, Margaret S (2004) Quantifying and comparing the accuracy of binary biomarkers when predicting a failure time outcome. Stat Med 23:1555-70
Moskowitz, Chaya S; Pepe, Margaret S (2004) Quantifying and comparing the predictive accuracy of continuous prognostic factors for binary outcomes. Biostatistics 5:113-27