Date of Award
Summer 8-1-2011
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Dr. Xu Zhang
Second Advisor
Dr. Gengsheng Qin
Third Advisor
Dr. Yichuan Zhao
Abstract
Many statistical methods for truncated data rely on the assumption that the failure and truncation time are independent, which can be unrealistic in applications. The study cohorts obtained from bone marrow transplant (BMT) registry data are commonly recognized as truncated samples, the time-to-failure is truncated by the transplant time. There are clinical evidences that a longer transplant waiting time is a worse prognosis of survivorship. Therefore, it is reasonable to assume the dependence between transplant and failure time. To better analyze BMT registry data, we utilize a Cox analysis in which the transplant time is both a truncation variable and a predictor of the time-to-failure. An inverse-probability-weighted (IPW) estimator is proposed to estimate the distribution of transplant time. Usefulness of the IPW approach is demonstrated through a simulation study and a real application.
DOI
https://doi.org/10.57709/2102085
Recommended Citation
Liu, Yang, "Analysis of Dependently Truncated Sample Using Inverse Probability Weighted Estimator." Thesis, Georgia State University, 2011.
doi: https://doi.org/10.57709/2102085