 |
English
|
正體中文
|
简体中文
|
Post-Print筆數 : 27 |
Items with full text/Total items : 110944/141864 (78%)
Visitors : 48022390
Online Users : 859
|
|
|
Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/75321
|
| Title: | Biomarker Selection in Medical Diagnosis |
| Authors: | Hsu, Man-Jen;Chang, Yuan-Chin Ivan;Hsueh, Huey-Miin
許嫚荏;張源俊;薛慧敏 |
| Contributors: | 統計系 |
| Keywords: | Biomarker selections;Confirmatory analysis;Discriminatory power;Receiver operating characteristic curves;Sensitivity and specificity;Statistical evidence;Statistical significance;Statistical testing;Diagnosis;Optimization;Biomarkers |
| Date: | 2013-06 |
| Issue Date: | 2015-05-26 18:16:58 (UTC+8) |
| Abstract: | A biomarker is usually used as a diagnostic or assessment tool in medical research. Finding a single ideal biomarker of a high level of both sensitivity and specificity is not an easy task; especially when a high specificity is required for a population screening tool. Combining multiple biomarkers is a promising alternative and can provide a better overall performance than the use of a single biomarker. It is known that the area under the receiver operating characteristic (ROC) curve is most popular for evaluation of a diagnostic tool. In this study, we consider the criterion of the partial area under the ROC curve (pAUC) for the purpose of population screening. Under the binormality assumption, we obtain the optimal linear combination of biomarkers in the sense of maximizing the pAUC with a pre-specified specificity level. Furthermore, statistical testing procedures based on the optimal linear combination are developed to assess the discriminatory power of a biomarker set and an individual biomarker, respectively. Stepwise biomarker selections, by embedding the proposed tests, are introduced to identify those biomarkers of statistical significance among a biomarker set. Rather than for an exploratory study, our methods, providing computationally intensive statistical evidence, are more appropriate for a confirmatory analysis, where the data has been adequately filtered. The applicability of the proposed methods are shown via several real data sets with a moderate number of biomarkers. © Springer Science+Business Media New York 2013. |
| Relation: | Springer Proceedings in Mathematics and Statistics, 55, 2013, 111-121, 21st Symposium of the International Chinese Statistical Association, ICSA 2012; Boston, MA; United States; 23 June 2012 到 26 June 2012; 代碼 100347 |
| Data Type: | conference |
| DOI 連結: | http://dx.doi.org/10.1007/978-1-4614-7846-1_10 |
| DOI: | 10.1007/978-1-4614-7846-1_10 |
| Appears in Collections: | [統計學系] 會議論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| index.html | | 0Kb | HTML2 | 1048 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
著作權政策宣告 Copyright Announcement1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.
2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(
nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(
nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
