Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM054438-01
Application #
2193802
Study Section
Special Emphasis Panel (ZRG7-STA (01))
Project Start
1996-05-01
Project End
1999-04-30
Budget Start
1996-05-01
Budget End
1997-04-30
Support Year
1
Fiscal Year
1996
Total Cost
Indirect Cost
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
075524595
City
Seattle
State
WA
Country
United States
Zip Code
98109
Kerr, Kathleen F; Brown, Marshall; Janes, Holly (2017) Reply to A.J. Vickers et al. J Clin Oncol 35:473-475
Kim, Soyoung; Huang, Ying (2017) Combining biomarkers for classification with covariate adjustment. Stat Med 36:2347-2362
Kerr, Kathleen F; Brown, Marshall D; Zhu, Kehao et al. (2016) Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use. J Clin Oncol 34:2534-40
Fong, Youyi; Yin, Shuxin; Huang, Ying (2016) Combining biomarkers linearly and nonlinearly for classification using the area under the ROC curve. Stat Med 35:3792-809
Pepe, Margaret S; Janes, Holly; Li, Christopher I et al. (2016) Early-Phase Studies of Biomarkers: What Target Sensitivity and Specificity Values Might Confer Clinical Utility? Clin Chem 62:737-42
Huang, Ying (2016) Evaluating and comparing biomarkers with respect to the area under the receiver operating characteristics curve in two-phase case-control studies. Biostatistics 17:499-522
Huang, Ying; Laber, Eric (2016) Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective. Stat Biosci 8:43-65
Pepe, Margaret Sullivan (2015) Response. J Natl Cancer Inst 107:356
Pepe, Margaret S; Fan, Jing; Feng, Ziding et al. (2015) The Net Reclassification Index (NRI): a Misleading Measure of Prediction Improvement Even with Independent Test Data Sets. Stat Biosci 7:282-295
Pepe, Margaret S; Li, Christopher I; Feng, Ziding (2015) Improving the quality of biomarker discovery research: the right samples and enough of them. Cancer Epidemiol Biomarkers Prev 24:944-50

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