자료유형 | 학위논문 |
---|---|
서명/저자사항 | Methods for Risk Markers that Incorporate Clinical Utility. |
개인저자 | Mishra, Anupam. |
단체저자명 | University of Washington. Biostatistics - Public Health. |
발행사항 | [S.l.]: University of Washington., 2019. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
형태사항 | 222 p. |
기본자료 저록 | Dissertations Abstracts International 81-02B. Dissertation Abstract International |
ISBN | 9781085695046 |
학위논문주기 | Thesis (Ph.D.)--University of Washington, 2019. |
일반주기 |
Source: Dissertations Abstracts International, Volume: 81-02, Section: B.
Advisor: Kerr, Kathleen K. |
이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
요약 | Risk markers are often used to help make clinical decisions. In this dissertation, we focus on developing statistical methods that account for the utility of a risk marker. We address problems of individualized decision-making, calibration, and combining multiple biomarkers when the ultimate goal is to use the combination for clinical decision-making. We review methods of estimating clinical utility from Bayesian and frequentist standpoints and draw connections between the two frameworks. We additionally consider the appropriateness of each framework to the individual decision-making problem. When existing risk models are applied to new populations, issues of miscalibration can arise. We propose two methods for recalibration that account for the clinical context in which the risk model will be used. Finally, we address the problem of combining risk markers into a single "composite" biomarker. We present a non-parametric method for developing linear combinations of risk markers that maximizes net benefit. We evaluate our methods using simulation studies and apply them to data from prostate cancer, cardiac disease, and diabetes studies. |
일반주제명 | Biostatistics. |
언어 | 영어 |
바로가기 |
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |