# Tagged Questions

Receiver Operating Characteristic, also known as ROC curve.

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### Adjusting for covariates in ROC curve analysis

This question is about estimating cut-off scores on a multi-dimensional screening questionnaire to predict a binary endpoint, in the presence of correlated scales. I was asked about the interest of ...
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### ROC curve for the same entries with different values

Maybe a silly question, but need your advice and comments. I have data entries (compounds) with two values, Value1 and Value2 (activity for two proteins). Is it meaningful to build the ROC curve for ...
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### How to do ROC-analysis in R with a Cox model

I've created a few Cox regression models and I would like to see how well these models perform and I thought that perhaps a ROC-curve or a c-statistic might be useful similar to this articles use: J. ...
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### What do ROC curves tell you that traditional inference wouldn't?

When would you tend to use ROC curves over some other tests to determine the predictive ability of some measurement on an outcome? When dealing with discrete outcomes (alive/dead, present/absent), ...
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### Validating a model for a set of DNA sequences

Consider a set of DNA sequences i.e. strings composed from the four letters A, C, G, T. We model these sequences as a random vector, $\mathbf{X}=(X_1,\dots, X_n)$. Each member of the set of ...
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### How to calculate sample size for comparing the area under the curve of two models?

Because I would like to calculate the sample size for comparing the area under the curve (AUC) of 2 models (cross-sectional study, predictor = continuous variable). Can you point me which function in ...
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### Tutorials for drawing an ROC curve

Are there tutorials you recommend that teach how to draw an ROC curve? Thanks.
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### How to draw an ROC curve?

If I have values for sensitivity and specificity for a group of studies, for example like this: ...
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### How to test the statistical significance of AUC?

(Step 1) Using my predictive model, I predicted 1000 scores for my sample dataset. (Step 2) I then calculate the random score using the same method for a randomized dataset. I firstly fit the ...
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### How do you generate ROC curves for leave-one-out cross validation?

When performing 5-fold cross-validation (for example), it is typical to compute a separate ROC curve for each of the 5 folds and often times a mean ROC curve with std. dev. shown as curve thickness. ...
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### Rationale of using AUC?

Especially in the computer-science oriented side of the machine learning literature, AUC (area under the receiver operator characteristic curve) is a popular criterion for evaluating classifiers. ...
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### ROC surfaces in R

If my response variable has 2 levels, 0 and 1, I can use a ROC curve to assess the accuracy of my predictive model. But what if my response variable has 3 levels, -1, 0, and 1? Is there a way to ...
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### ROC plot for continuous data in R

I am currently estimating a bunch of ARMA models, and using them to predict subsets of my data. In order to evaluate their predictive accuracy I would like to make some ROC plots, however since all of ...