Date of Award
12-2009
Degree Name
Doctor of Philosophy
Department
Statistics
First Advisor
Dr. Joshua D. Naranjo
Second Advisor
Dr. Joseph McKean
Third Advisor
Dr. Jung-Chao Wang
Fourth Advisor
Dr. Steven Denham
Abstract
It has been shown that under a location-scale model y = μ + βz + σε at where y is right censored, the Log-Rank test is asymptotically efficient for the Extreme minimum value error distribution while Peto and Peto's Wilcoxon test is asymptotically efficient for the Logistic error distribution. We propose a two-sample adaptive test, which first selects between Extreme minimum value and Logistic error distribution as to which is a better fit to the data, then performs the asymptotically efficient test (Log-Rank or Peto and Peto's Wilcoxon test) for the selected distribution. The performance of the adaptive test is compared with the Log-Rank and Peto and Peto's Wilcoxon tests through simulation.
Access Setting
Dissertation-Open Access
Recommended Citation
Tordilla, Annie A., "A Two-Sample Adaptive Procedure Based on the Log-Rank and Peto and Peto's Wilcoxon Tests" (2009). Dissertations. 726.
https://scholarworks.wmich.edu/dissertations/726