This project will continue the development of statistical methodology useful in the design and analysis of studies involving censored survival data. Emphasis will also be given to the evaluation of the large and small sample behavior of newly proposed procedures and of other existing techniques. Methods used will include asymptotic theory for statistical tests, Monte Carlo simulations, and numerical analysis. In the area of linear and non-linear rank test procedures, four important issues will be addressed: (a) the development and evaluation of K-sample omnibus test procedures based upon non-linear rank supremum-type statistics; (b) development and evaluation of one-sample tests of location which can be employed in the two-sample match pair survival problem involving possibly unequal censoring distribution; (c) evaluation of efficiencies and general properties of a board class of linear rank statistics which include the log rank, Pto-Peto Wilcoxon, and Harrington-Fleming Gp class as special cases; and (d) the investigation of large and small sample properties of previously and newly proposed rank statistics when sample sizes or censoring distributions are unequal. Large and small sample properties of the Cox proportional hazards regression model will also be investigated. Special attention will be given to the effects of: (a) over or under parameterization of the model, (b) heterogeneity in the data, and (c) model reduction techniques. Finally, a formal study of the large sample efficiencies of recently proposed group sequential linear rank procedures will be performed.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA039929-03
Application #
3179299
Study Section
(SSS)
Project Start
1984-09-01
Project End
1987-12-31
Budget Start
1987-01-01
Budget End
1987-12-31
Support Year
3
Fiscal Year
1987
Total Cost
Indirect Cost
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
02115
Huang, Jie; Harrington, David (2005) Iterative partial least squares with right-censored data analysis: a comparison to other dimension reduction techniques. Biometrics 61:17-24
Peckova, Monika; Fleming, Thomas R (2003) Adaptive test for testing the difference in survival distributions. Lifetime Data Anal 9:223-38
Huang, Jie; Harrington, David (2002) Penalized partial likelihood regression for right-censored data with bootstrap selection of the penalty parameter. Biometrics 58:781-91
Xu, R; Harrington, D P (2001) A semiparametric estimate of treatment effects with censored data. Biometrics 57:875-85
Jones, C L; Harrington, D P (2001) Omnibus tests of the martingale assumption in the analysis of recurrent failure time data. Lifetime Data Anal 7:157-71
Xu, R; Adak, S (2001) Survival analysis with time-varying relative risks: a tree-based approach. Methods Inf Med 40:141-7
Bernardo, M V; Harrington, D P (2001) Sample size calculations for the two-sample problem using the multiplicative intensity model. Stat Med 20:557-79
Patricia Bernardo , M V; Ibrahim, J G (2000) Group sequential designs for cure rate models with early stopping in favour of the null hypothesis. Stat Med 19:3023-35
Lin, D Y; Psaty, B M; Kronmal, R A (1998) Assessing the sensitivity of regression results to unmeasured confounders in observational studies. Biometrics 54:948-63
Gray, R J (1998) On tests for group variation with a small to moderate number of groups. Lifetime Data Anal 4:139-48

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