ROC curve for Hemoglobin in study population (N= 100)
What is an ROC curve?
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Non-parametric estimation of ROC curve
... the study. Moreover, the most commonly used index of the ROC curve, called the area under the curve (AUC), can be interpreted as the probability of Y greater than X, which can be easily ...
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Generalization Bounds for the Area Under an ROC Curve
... Our uniform convergence bound applies to learned ranking functions chosen from general (pos- sibly infinite) function classes. The bound is expressed in terms of a new set of combinatorial parameters that we have termed ...
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Generalization Bounds for the Area Under the ROC Curve
... We study generalization properties of the area under the ROC curve (AUC), a quantity that has been advocated as an evaluation criterion for the bipartite ranking ...
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Empirical Likelihood Inference for the Area Under the ROC Curve
... patients with MM. The study sample consists of 21 patients with MM and 51 patients with benign melanocytic lesions, and the gold standard used in the study is biopsy. Because the distributions of the ...
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Regression Analysis for the Partial Area Under the ROC Curve
... ence population as all 60-year old disease-free men with PSA value exceeding its correspond- ing th percentile, there is a & & & ( *& & chance that a randomly selected 60-year old man with cancer whose PSA is ...
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Smoothed jackknife empirical likelihood method for ROC curve
... a b s t r a c t In this paper we propose a smoothed jackknife empirical likelihood method to construct confidence intervals for the receiver operating characteristic (ROC) curve. By applying the standard ...
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The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling
... Complex genetic diseases Table 1 lists AUC max for a range of complex genetic diseases calculated using equation 3, with h 2 L calculated using equation 1 from published estimates of K and l S . Despite being observable, ...
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Optimal Weights in Nonparametric Analysis of Clustered ROC Curve Data
... In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed. For example, in a study by Masaryk et al. (1991) [2], two radiologists evaluated 65 carotid arteries (left ...
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nsROC: An R package for Non-Standard ROC Curve Analysis
... Non-Standard ROC Curve Analysis by Sonia Pérez-Fernández, Pablo Martínez-Camblor, Peter Filzmoser and Norberto Corral Abstract The receiver operating characteristic (ROC) curve is a graphical ...
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Combining Predictors for Classification using the Area Under the ROC Curve
... Weighting the misclassification probabilities according to the population prevalence of cases should perhaps be considered. Although we have made a case for optimizing the AUC to combine markers, much work remains ...
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Hemoglobin and mortality in patients with COPD: a nationwide population-based cohort study
... general population. Our study also included a larger number of COPD patients with long-term follow-up compared with previous ...COPD population who do not require oxygen therapy, hospitalization, or ...
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COMPARING SEVERAL DIAGNOSTIC PROCEDURES USING THE INTRINSIC MEASURES OF ROC CURVE
... Results and discussion To illustrate the above proposed methodology, a data set of Parathyroid Disease is used (Zhou. et. al. (2011)). Parathyroid glands are small endocrine glands usually located in the neck or upper ...
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ROC curve analyses of eyewitness identification decisions: An analysis of the recent debate
... etical ROC. The theoretical ROC for a given measure simply connects all combinations of hit and false alarm rates that yield the same accuracy value according to that measure, regardless of differences in ...
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Evaluation of diagnostic performance using partial area under the roc curve
... Here, we term this index as the “standardized partial AUC” (spAUC). For ROC curves describing better-than-chance performance, A e varies from 0.5 to 1 regardless of e, and for e=1 it reduces to the conventional ...
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Evaluation of Area under the Constant Shape Bi-Weibull ROC Curve
... a ROC model developed from two parameter Weibull distributions for evaluating the accuracy of biomarkers in predicting disease ...Bi-Weibull ROC curve is a main objective for this ...
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Accurate likelihood inference on the area under the ROC curve for small sample.
... dierent ombinations of sample sizes (n 1 , n 2 ) . The simulation study was repeated for ψ = 0.8 and ψ = 0.95 . T able 1 reports empirial overages for the equitailed ondene intervals for A with ...
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Evaluation of biomarker using two parameter bi-exponential ROC curve
... the ROC curve is plotted, it is important to study the properties of it, in order to highlight some key understanding from the ...parametric ROC curve must satisfy the basic three ...
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Estimation of area under the ROC curve under nonignorable verification bias
... The new method makes parametric assumptions on the verification probability, and the probability of being diseased for verified samples rather than for the whole sample. The proposed parametric assumption on the observed ...
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Controlling for Confounding when Association is Quantified by Area Under the ROC Curve
... 4.5 Results of the simulation study Results of the simulation study are given in Tables 4.6 to 4.10 and Figures 4.3 to 4.7. When we examined the impact of missing influential covariates in Aim 1, the ...
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