Project Details
Description
(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.
Status | Finished |
---|---|
Effective start/end date | 12/1/84 → 1/1/90 |
Funding
- National Institute of General Medical Sciences
ASJC Scopus Subject Areas
- Statistics and Probability
- Medicine(all)
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