Related references
Note: Only part of the references are listed.A unified inference procedure for a class of measures to assess improvement in risk prediction systems with survival data
Hajime Uno et al.
STATISTICS IN MEDICINE (2013)
Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them)
Daniel Berrar et al.
BRIEFINGS IN BIOINFORMATICS (2012)
Adjusting confounders in ranking biomarkers: a model-based ROC approach
Tao Yu et al.
BRIEFINGS IN BIOINFORMATICS (2012)
A comparison of estimators to evaluate the discriminatory power of time-to-event models
Matthias Schmid et al.
STATISTICS IN MEDICINE (2012)
Ranking prognosis markers in cancer genomic studies
Shuangge Ma et al.
BRIEFINGS IN BIOINFORMATICS (2011)
Using cross-validation to evaluate predictive accuracy of survival risk classifiers based on high-dimensional data
Richard M. Simon et al.
BRIEFINGS IN BIOINFORMATICS (2011)
Added predictive value of high-throughput molecular data to clinical data and its validation
Anne-Laure Boulesteix et al.
BRIEFINGS IN BIOINFORMATICS (2011)
An evaluation of resampling methods for assessment of survival risk prediction in high-dimensional settings
Jyothi Subramanian et al.
STATISTICS IN MEDICINE (2011)
On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data
Hajime Uno et al.
STATISTICS IN MEDICINE (2011)
Assessing the Performance of Prediction Models A Framework for Traditional and Novel Measures
Ewout W. Steyerberg et al.
EPIDEMIOLOGY (2010)
Evaluating the ROC performance of markers for future events
Margaret S. Pepe et al.
LIFETIME DATA ANALYSIS (2008)
Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series
Christine Desmedt et al.
CLINICAL CANCER RESEARCH (2007)
Evaluating prediction rules for t-year survivors with censored regression models
Hajime Uno et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2007)
Estimation of time-dependent area under the ROC curve for long-term risk prediction
Lloyd E. Chambless et al.
STATISTICS IN MEDICINE (2006)
Cross-validated Cox regression on microarray gene expression data
Hans C. van Houwelingen et al.
STATISTICS IN MEDICINE (2006)
CASPAR: a hierarchical bayesian approach to predict survival times in cancer from gene expression data
Lars Kaderali et al.
BIOINFORMATICS (2006)
The sensitivity and specificity of markers for event times
TX Cai et al.
BIOSTATISTICS (2006)
A time-dependent discrimination index for survival data
L Antolini et al.
STATISTICS IN MEDICINE (2005)
Concordance probability and discriminatory power in proportional hazards regression
M Gönen et al.
BIOMETRIKA (2005)
Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data
J Gui et al.
BIOINFORMATICS (2005)
Survival model predictive accuracy and ROC curves
PJ Heagerty et al.
BIOMETRICS (2005)
Gene-expression pro-files to predict distant metastasis of lymph-node-negative primary breast cancer
YX Wang et al.
LANCET (2005)
Gene expression signature of fibroblast serum response predicts human cancer progression: Similarities between tumors and wounds
HY Chang et al.
PLOS BIOLOGY (2004)
Partial Cox regression analysis for high-dimensional microarray gene expression data
Hongzhe Li et al.
BIOINFORMATICS (2004)
Good Old clinical markers have similar power in breast cancer prognosis as microarray gene expression profilers
P Edén et al.
EUROPEAN JOURNAL OF CANCER (2004)
Explained variation and predictive accuracy in general parametric statistical models: The role of model misspecification
S Rosthoj et al.
LIFETIME DATA ANALYSIS (2004)
A gene-expression signature as a predictor of survival in breast cancer.
MJ van de Vijver et al.
NEW ENGLAND JOURNAL OF MEDICINE (2002)
Gene expression profiling predicts clinical outcome of breast cancer
LJ van't Veer et al.
NATURE (2002)