The aim of the training program in cancer biostatistics is to educate predoctoral and postdoctoral students in statistical theory and methods as applied in laboratory, clinical, and epidemiological studies who can become the future leaders in biostatistical and collaborative cancer research. Clinical and basic science investigators in cancer research with positions in academia, government, and industry have increasingly sought biostatistical expertise over the past three decades. However, the number of trained individuals has not adequately kept up with the demand. In training biostatisticians, this program will take advantage of the strong tradition at the University of Wisconsin in the Statistics Department, which is known for combining both theory and application in statistical research, in the University of Wisconsin Comprehensive Cancer Center (UWCCC), which has long recognized the value of statistical expertise, and in the Department of Biostatistics and Medical Informatics. The Department of Biostatistics, created to foster biostatistics research and collaboration with medical investigators, provides the critical interaction between the Statistics Department and the University of Wisconsin Comprehensive Cancer Center. Currently, nine out of the fifteen faculty members of the Department of Biostatistics and Medical Informatics have joint appointments in the UWCCC. Nine also have joint appointments with the Department of Statistics. The Statistics Department awards an M.S. and Ph.D. in Statistics with emphasis in Biostatistics. Predoctoral trainees will be expected to have completed a baccalaureate degree with a major in mathematics, statistics, or computer science. All predoctoral trainees must be graduate students in Statistics to be eligible. Selection into this training program will be made by the Biostatistics Committee, based on academic records, Graduate Record Examination scores, and recommendations by the Statistics Department Admission Committee. Students must fulfill all the usual Ph.D. Statistics degree requirements plus complete additional courses in biostatistics. They will also obtain practical experience by attending various colloquia in the UWCCC and by participating in consulting projects in cancer. Continued support for four predoctorates and one postdoctorate is proposed. A faculty mentor on specific cancer related projects as well as is/her own statistical research. A new addition to this proposal is to develop a course in statistical methods for genetics and molecular biology research.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Institutional National Research Service Award (T32)
Project #
5T32CA009565-13
Application #
6375535
Study Section
Subcommittee G - Education (NCI)
Project Start
1988-06-01
Project End
2004-05-31
Budget Start
2001-06-01
Budget End
2002-05-31
Support Year
13
Fiscal Year
2001
Total Cost
$110,042
Indirect Cost
Name
University of Wisconsin Madison
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Stanhope, Stephen A; Sengupta, Srikumar; den Boon, Johan et al. (2009) Statistical use of argonaute expression and RISC assembly in microRNA target identification. PLoS Comput Biol 5:e1000516
Kendziorski, C M; Newton, M A; Lan, H et al. (2003) On parametric empirical Bayes methods for comparing multiple groups using replicated gene expression profiles. Stat Med 22:3899-914
Newton, M A; Kendziorski, C M; Richmond, C S et al. (2001) On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data. J Comput Biol 8:37-52
Lan, H; Kendziorski, C M; Haag, J D et al. (2001) Genetic loci controlling breast cancer susceptibility in the Wistar-Kyoto rat. Genetics 157:331-9
Kosorok, M R; Qu, R (1999) Exact simultaneous confidence bands for a collection of univariate polynomials in regression analysis. Stat Med 18:613-20
Petereit, D G; Sarkaria, J N; Potter, D M et al. (1999) High-dose-rate versus low-dose-rate brachytherapy in the treatment of cervical cancer: analysis of tumor recurrence--the University of Wisconsin experience. Int J Radiat Oncol Biol Phys 45:1267-74
Gange, S J; Linton, K L; Scott, A J et al. (1995) A comparison of methods for correlated ordinal measures with ophthalmic applications. Stat Med 14:1961-74
Richardson, D J (1992) Withdrawal censoring and the sequential logrank procedure. Stat Med 11:1359-66