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Parametric inference on quantile residual life

Ghebrehawariat, Kidane (2016) Parametric inference on quantile residual life. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

The need for residual life analysis arises in many fields including medicine and life testing. For instance, in medicine, a clinician and a patient would be interested in knowing by how long a new drug can extend the life span of that patient. Problems in remaining life time after surviving up to a certain time are often framed and addressed statistically in terms of mean, hazard rate or quantile. The quantile approach enjoys some practical advantages over the other approaches such as robustness, ease of interpretation, and existence. Most of the methodological work on quantile residual life in the literature has been semi-parametric or non-parametric. However, parametric approaches are expected to be optimal or asymptotically efficient under a correct specification of the model. Furthermore, the parametric approach does not require nonparametric estimation of the probability density function of the underlying distribution under informative or noninformative censoring to evaluate the variance of the quantile estimator. In this dissertation, parametric inference procedures for the quantile residual life under competing and non-competing risks settings are developed for the one-sample, two-sample and regression cases. We adopt the accelerated failure time (AFT) framework to incorporate covariates for the regression case. The finite sample properties of the proposed methods are studied through extensive simulations. The simulation results indicate that the proposed methods perform well. The proposed methods are applied to a breast cancer data.
PUBLIC HEALTH SIGNIFICANCE: The results established in this dissertation will provide new parametric methods to researchers and investigators in public health who conduct quantile residual life analysis, which will facilitate efficient communication between researchers and stakeholders regarding the efficacy of new interventions.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ghebrehawariat, Kidanekig11@pitt.eduKIG11
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairJeong, Jong-Hyeonjjeong@pitt.eduJJEONG
Committee CoChairDing, Yingyingding@pitt.eduYINGDING
Committee MemberNormolle, Danieldpn7@pitt.eduDPN7
Committee Membercheng, yuyucheng@pitt.eduYUCHENG
Date: 27 January 2016
Date Type: Publication
Defense Date: 1 December 2015
Approval Date: 27 January 2016
Submission Date: 23 November 2015
Access Restriction: 3 year -- Restrict access to University of Pittsburgh for a period of 3 years.
Number of Pages: 85
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Biostatistics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Quantile residual life, Parametric, Breast Cancer, Competing Risk, Accelerated Failure Time
Date Deposited: 27 Jan 2016 21:55
Last Modified: 01 Jan 2019 06:15
URI: http://d-scholarship.pitt.edu/id/eprint/26428

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