The long-term goal of this research grant is to bring new developments in statistical theory and methodology to bear on the practical problems of biostatistics and medicine. The researchers pursue this goal from their joint positions in the Stanford medical school, where they work on specific biostatistical projects, and the development and review. Research on the grant involves the creation of new statistical methods, study of new and existing techniques through mathematical analysis and computer simulation, and trial applications of these procedures to ongoing research projects at the medical school. The following five areas will be the focus of the research: (1) bootstrap methods, (2) recursive partitioning and classification trees, (3) modern regression methods and their extensions, (4) image reconstruction methods, (5) hazard rates and censored data. Successful new statistical methodology finds application across a wide spectrum of biomedical applications. On the basis of past experience, the topics studied here will be particularly useful in cancer therapy clinical trials, cardiovascular research, and areas like gait analysis where diagnostic measures tend to have very complicated structure.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM021215-16
Application #
3270337
Study Section
Special Emphasis Panel (SSS (C))
Project Start
1977-07-01
Project End
1992-11-30
Budget Start
1990-12-01
Budget End
1991-11-30
Support Year
16
Fiscal Year
1991
Total Cost
Indirect Cost
Name
Stanford University
Department
Type
Schools of Arts and Sciences
DUNS #
800771545
City
Stanford
State
CA
Country
United States
Zip Code
94305
Whittemore, A S; Halpern, J (1994) A class of tests for linkage using affected pedigree members. Biometrics 50:118-27
Whittemore, A S; Halpern, J (1994) Probability of gene identity by descent: computation and applications. Biometrics 50:109-17
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