(i) To develop optimal sequential testing and estimation procedures for biomedical data in general and censored survival data in particular. (ii) To find efficient design of clinical trials for comparing two treatments, incorporating the scientific, economic and ethical considerations. (iii) To compare the linear and general empirical Bayes approaches to estimating many parameters (means, variances, etc.) and to construct adaptive empirical Bayes estimators that will combine the best features of both. To extend empirical Bayes methods to completely nonparametric problems. To construct tests based on empirical Bayes prediction intervals for the efficacy of a medical treatment without the necessity of using a control group. (iv) To develop and apply pattern recognition and nonparametric classification techniques for certain clinical problems. (v) To develop stochastic approximation and other techniques for bioassay and dosage determination.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM027976-04A1
Application #
3275226
Study Section
(SSS)
Project Start
1980-07-01
Project End
1987-11-30
Budget Start
1984-12-01
Budget End
1985-11-30
Support Year
4
Fiscal Year
1985
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Type
Graduate Schools
DUNS #
064931884
City
New York
State
NY
Country
United States
Zip Code
10027