Pages that link to "Item:Q3087593"
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The following pages link to Selection and combination of biomarkers using ROC method for disease classification and prediction (Q3087593):
Displaying 17 items.
- Linear biomarker combination for constrained classification (Q66424) (← links)
- A PAUC-based estimation technique for disease classification and biomarker selection (Q461666) (← links)
- Robust and efficient estimation for the treatment effect in causal inference and missing data problems (Q1644251) (← links)
- Estimating a unitary effect summary based on combined survival and quantitative outcomes (Q1800122) (← links)
- The covariate-adjusted ROC curve: the concept and its importance, review of inferential methods, and a new Bayesian estimator (Q2092897) (← links)
- Improving the classification accuracy using biomarkers selected from machine learning methods (Q2138945) (← links)
- A copula-based method of classifying individuals into binary disease categories using dependent biomarkers (Q2220308) (← links)
- ROC representation for the discriminability of multi-classification markers (Q2417831) (← links)
- Construction of leading economic index for recession prediction using vine copulas (Q2700564) (← links)
- Identifying optimal biomarker combinations for treatment selection via a robust kernel method (Q3465367) (← links)
- Combining Multiple Biomarker Models in Logistic Regression (Q3506487) (← links)
- Is it even rainier in<i>North</i>Vancouver? A non-parametric rank-based test for semicontinuous longitudinal data (Q5036576) (← links)
- Combining biomarkers by maximizing the true positive rate for a fixed false positive rate (Q6091667) (← links)
- A generalized single‐index linear threshold model for identifying treatment‐sensitive subsets based on multiple covariates and longitudinal measurements (Q6180923) (← links)
- Supervised structural learning of semiparametric regression on high-dimensional correlated covariates with applications to eQTL studies (Q6626836) (← links)
- Developing biomarker combinations in multicenter studies via direct maximization and penalization (Q6627627) (← links)
- Marginal, conditional, and pseudo likelihood ratio approaches for biomarker combination to predict a binary disease outcome (Q6628395) (← links)
