Six specific statistical research areas have been identified which are of a general nature and relate to issues in the data analysis of clinical and laboratory research from the Wisconsin Clinical Cancer Center or from cancer research in general. 1. Analysis of Censored Survival Data a) Nonparametric Regression Analysis b) Robust Estimation for Linear Models c) Discrete Time Survival Estimates with Time-Dependent Covariates 2. Clinical Trial Data Monitoring a) Group Sequential Methods b) Stochastic Curtailed Sampling 3. Goodness of Fit a) Asymptotic Properties for a Large Class of Tests b) Minimum Distance Estimation for Multinomial Probabilities c) Proportional Hazard Models 4. Selected Sampling in Regression Analysis 5. Stratified Randomization vs. Non-Stratified Randomization 6. Other Research Problems The investigators will interact with each other in this research but individuals will be primarily responsible for various aspects. Statistical methodology will be used including large sample theory, normal theory, numerical integration, Monte Carlo methods, and graphical techniques using the Department of Statistics' VAX/750 computer. Objectives are the development of more appropriate or improved methods for the analysis of data in the general medical research setting with exportable computer software as needed.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA018332-12
Application #
3164928
Study Section
(SSS)
Project Start
1978-07-01
Project End
1987-06-30
Budget Start
1986-07-01
Budget End
1987-06-30
Support Year
12
Fiscal Year
1986
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Chen, Y H Joshua; DeMets, David L; Lan, K K Gordon (2004) Increasing the sample size when the unblinded interim result is promising. Stat Med 23:1023-38
Fleming, T R; DeMets, D L (1996) Surrogate end points in clinical trials: are we being misled? Ann Intern Med 125:605-13
Lindstrom, M J (1995) Self-modelling with random shift and scale parameters and a free-knot spline shape function. Stat Med 14:2009-21
Lee, J W; DeMets, D L (1995) Group sequential comparison of changes: ad-hoc versus more exact method. Biometrics 51:21-30
Lindstrom, M J; Kunugi, K A; Kinsella, T J (1993) Global comparison of radiation and chemotherapy dose-response curves with a test for interaction. Radiat Res 135:269-77
Kim, K; Demets, D L (1992) Sample size determination for group sequential clinical trials with immediate response. Stat Med 11:1391-9
Palta, M; Yao, T J (1991) Analysis of longitudinal data with unmeasured confounders. Biometrics 47:1355-69
Lindstrom, M L; Bates, D M (1990) Nonlinear mixed effects models for repeated measures data. Biometrics 46:673-87
Lan, K K; DeMets, D L (1989) Changing frequency of interim analysis in sequential monitoring. Biometrics 45:1017-20
Storer, B E (1989) Design and analysis of phase I clinical trials. Biometrics 45:925-37

Showing the most recent 10 out of 17 publications