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Inference on Competing Risks in Breast Cancer Data

Haile, Sarah R (2008) Inference on Competing Risks in Breast Cancer Data. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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While nonparametric methods have been well established for inference on competing risks data, parametric methods for such data have not been developed as much. Because the cumulative incidence functions are improper by their nature, flexible distribution families accommodating improperness are needed for modeling competing data more accurately. Additionally, different types of events present in a competing risks setting may be correlated, yet current inference methods do not permit inferring such data taking into account the correlation between failure time distributions. This work first presents two new distributions which are well-suited for modeling competing risks data. In existing inference procedures for competing risks data, it appears that the correlation between failure time distributions of competing events are fixed as a constant. In the second part of this dissertation, a novel approach is proposed which allows researchers to model competing risks data by taking the correlation into account by estimating it. The methods are illustrated by analyzing survival data from a breast cancer trial of the National Surgical Adjuvant Breast and Bowel Project. Simulation studies are also presented for each of the proposed new distributions.Public Health Significance: Competing risks occur often in many clinical studies, and must be accounted for whenever researchers are interested in only one type of event. For example, researchers may be interested in investigating only local recurrences of breast cancer, but must also take into account all other possible types of events as competing. Parametric methods are not currently as well established as other methods for competing risks data. Development of flexible parametric inference procedures suitable for modeling competing risks data would provide more accurate information, which will serve to improve patient care in clinical settings.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Haile, Sarah
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairJeong, Jong-Hyeonjeong@nsabp.pitt.eduJJEONG
Committee MemberWahed, AbdusWahedA@edc.pitt.eduWAHED
Committee MemberChang, Chung-Chou
Committee MemberCostantino, Joseph Pcostantino@nsabp.pitt.eduCOSTAN
Date: 28 September 2008
Date Type: Completion
Defense Date: 22 July 2008
Approval Date: 28 September 2008
Submission Date: 22 July 2008
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Biostatistics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Competing Risks; Cumulative Incidence; Breast Cancer; Survival Analysis
Other ID:, etd-07222008-143547
Date Deposited: 10 Nov 2011 19:52
Last Modified: 15 Nov 2016 13:46


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