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A Simple Locally Efficient Estimator For Relative Risk In Case-Cohort Studies

Sampene, Emmanuel (2014) A Simple Locally Efficient Estimator For Relative Risk In Case-Cohort Studies. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

A case-cohort study is a two-phase study where at the first phase a representative sample, referred to as the study cohort, is selected from the target population. At the second phase, a subsample is selected from the cohort based on the case status. All cases are included in the subsample whereas only a random sample of controls is included. The endpoint of interest in such studies is usually the failure time. Several methods have been proposed to estimate the relative risk or hazard ratio from a case-cohort study. These methods almost always disregard the covariate information that is not included in the sampled study sub-cohort, and therefore, results in the loss of efficiency. While there have been attempts to derive the most efficient estimators, the resulting estimators were challenging from the data analysis point of view. We propose a locally efficient estimator (LEE) by restricting the estimator to a class of regular asymptotically linear estimators. The properties of this estimator are investigated through simulation and application to the Wilm's tumor study. The public health relevance of this dissertation is the use of innovative methodology to reduce cost associated with research.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Sampene, Emmanuelems120@pitt.eduEMS120
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairWahed, Abdus S.wahed@pitt.eduWAHED
Committee MemberArena, Vincent C.arena@pitt.eduARENA
Committee MemberChang, Chung Chouchangj@pitt.eduCHANGJ
Committee MemberJeong, Jong-Hyeonjeong@nsabp.pitt.eduJJEONG
Committee MemberMurugan, Raghavanmuruganr@ccm.upmc.eduRAM53
Date: 31 January 2014
Date Type: Publication
Defense Date: 14 November 2013
Approval Date: 31 January 2014
Submission Date: 5 December 2013
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 69
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: Case-cohort study; Influence Function; Martingale theory; Regular asymptotically linear estimator; Two-stage design
Date Deposited: 31 Jan 2014 16:17
Last Modified: 01 Jan 2019 06:15
URI: http://d-scholarship.pitt.edu/id/eprint/20221

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