Considering the number of measures that must be met, 35 candidate definitions were created and tested using receiver operating characteristic curves (ROC) for sensitivity and specificity. (bmj.com)
Receiver operating characteristics (ROC) curves were obtained and the sensitivity, specificity, positive, and negative predictive values were calculated for different cut-off scores on each rating scale. (nih.gov)
Using individual SR exposure as the reference, Area Under the Curve (AUC) of Receiver Operating Characteristic (ROC) curves, sensitivity, and specificity were calculated. (cdc.gov)
In systematic reviews comparing vibration controlled transient elastography (VCTE TM ) to biopsy (as a gold standard) for the detection of severe liver fibrosis, the mean area under the receiver operating characteristic (ROC) curve was 0.89 (95% CI, 0.88-0.91) (Tsochatzis et al, 2011, Friedrich-Rust et al, 2008) and the overall sensitivity and specificity were 82% (95% CI, 78-86%) and 86% (95% CI 0.80-0.91). (cdc.gov)
Receiver opera3
Receiver-operating characteristic curve for ability of association of serum cholinesterase activity with mortality. (ajtmh.org)
The PAWS score area under the receiver operating characteristic curve was 0.86. (bmj.com)
The area under the receiver operating characteristic curve was 0.806. (bmj.com)
Thresholds3
A contingency table has been calculated at a single threshold and information about other thresholds has been lost. (stackexchange.com)
ROC curves with few thresholds significantly underestimate the true area under the curve (1). (stackexchange.com)
Receiver-operating characteristic plots determined thresholds for each model, and the area under the curve was used to compare methods. (cdc.gov)
Logistic regression3
I am using the following code to plot the ROC curve after having run the logistic regression. (stackoverflow.com)
I am interested in calculating area under the curve (AUC), or the c-statistic, by hand for a binary logistic regression model. (stackexchange.com)
Receiver-operating characteristic (ROC) curves derived from logistic regression analysis were used to determine the classification performance for each analyte. (biomedcentral.com)
Characteristics3
Receiver operating characteristics (ROC) curves were calculated to assess the discrimination of PMEWS. (bmj.com)
75 to define limited literacy, we plotted receiver-operating characteristics (ROC) curves and calculated likelihood ratios for cutoff scores on the new instrument. (annfammed.org)
We used ROC, Matthew's correlation coefficient and RMSD to determine the overall performance characteristics. (biomedcentral.com)
Plot6
I want to create a roc object by using the function 'roc' of pROC package in R, and plot the roc object. (stackoverflow.com)
Is it possible to insert a line of no discrimination in ROC plot using ggroc? (stackoverflow.com)
I have created a ROC plot with multiple ROC-curves using ggroc based on pROC. (stackoverflow.com)
for plotting the equivalent curves with the general R plot. (rdrr.io)
Plot the receiver-operator characteristic (ROC) curve to visualize the accuracy of a diagnostic test. (analyse-it.com)
The value a can be used to plot a summary ROC (SROC) curve. (wikipedia.org)
Confidence interval2
How to draw multiple roc curves with confidence interval in pROC? (stackoverflow.com)
CDS-12 was more strongly associated than FTND with DSM-defined dependence measured by MINI: area under the Receiver Operating Characteristic (ROC) curve=0.72 (95% confidence interval=0.70-0.73). (who.int)
0.882
Area under the ROC curve is 0.88 for English and 0.72 for Spanish versions. (annfammed.org)
Based on the regression coefficient and the expression value of each selected gene obtained by the multivariate Cox regression model, the risk score of each patient was calculated, then we separated 17 patients into high-risk and low-risk groups using the median risk score as the cutoff. (hindawi.com)
Time to peak and peak thrombin followed an exponential regression curve, while this was linear for the endogenous thrombin potential (ETP). (researchsquare.com)
Area under the receiver2
Prognostic accuracy [area under the receiver operating characteristic (ROC) curve (AUC)] and Uno's cumulative/time-dependent C-statistics (uAUC) were calculated for 1-, 3-, and 5-year mortality. (lu.se)
the area under the receiver operator characteristic [ROC] curve was 0.7231. (medscape.com)
Confusion matrix2
You can technically calculate a ROC AUC for a binary classifier from the confusion matrix. (stackexchange.com)
Consider a test with the following 2×2 confusion matrix: We calculate the diagnostic odds ratio as: DOR = T P / F P F N / T N = 26 / 12 3 / 48 = 34.666 … ≈ 35 {\displaystyle {\text{DOR}}={\frac {TP/FP}{FN/TN}}={\frac {26/12}{3/48}}=34.666\ldots \approx 35} This diagnostic odds ratio is greater than one, so we know that the test is discriminating correctly. (wikipedia.org)
Time-dependent1
The accuracy of the prediction model was evaluated by time-dependent ROC analysis. (hindawi.com)
Threshold2
The receiver operating characteristic (ROC) curve represents the range of tradeoffs between true-positive and false-positive classifications as one alters the threshold for making that choice from the model. (stackexchange.com)
If the probability of the calculated statistic is greater than the removal threshold value, the variable is removed from the model. (xlstat.com)
Admission1
PAWS scores were calculated retrospectively for 46 consecutive children who required admission from the ED to the paediatric intensive care unit (PICU) and for 49 control children who were admitted from the ED to the general paediatric ward. (bmj.com)
Accuracy2
ROC curve analysis showed that, compared with the clinical model (model 1), the combined model with MRS (model 2) significantly improved the diagnostic accuracy of MI in patients with EC (area under the curve in model 1 vs. model 2: 0.737 vs. 0.828 in the training cohort and 0.713 vs. 0.759 in the validation cohort). (spandidos-publications.com)
[ 13-15 ] However, the direct measurement of serum free cortisol requires laborious laboratory techniques that are not commonly available, and the accuracy of calculated free cortisol [ 13 , 14 ] is not widely accepted. (medscape.com)
Analysis5
How to deal with multiple class ROC analysis in R (pROC package)? (stackoverflow.com)
How to get p value after ROC analysis with pRoc package? (stackoverflow.com)
After ROC analysis of a set of data, how to calculate p-value? (stackoverflow.com)
The area under the curve (AUC) was 0.75 calculated by the ROC curve analysis. (hindawi.com)
A calibration curve, a receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the effectiveness of the nomogram. (spandidos-publications.com)
Probability1
Use probability theory under the Bayesian framework for calculating the risk of selecting candidates in a multi-environment context [Dias et al. (eddelbuettel.com)
Commonly2
The second data set was used to calculate were most commonly used. (lu.se)
Typically, such quantitative test results (eg, white blood cell count in cases of suspected bacterial pneumonia) follow some type of distribution curve (not necessarily a normal curve, although commonly depicted as such). (msdmanuals.com)
When I use multiclass.roc function in R (pROC package), for instance, I trained a data set by random forest, here is my code: # randomForest & pROC packages should be installed: # install. (stackoverflow.com)
for converting a curves and points object to a data frame. (rdrr.io)
So if one, in the data file, specify the standard deviation one must be sure to set fac to the number of data points on which the average was calculated. (lu.se)
Scores3
The patient report forms were reviewed for the PMEWS variables and scores calculated using the PMEWS system. (bmj.com)
Risk scores were calculated using the original Swedish Pulmonary. (lu.se)
Risk scores were calculated using the original Swedish Pulmonary Arterial Hypertension Registry (SPAHR)/Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) three-strata model, the updated SPAHR three-strata model with divided intermediate risk, and the simplified three-parameter COMPERA 2.0 four-strata model. (lu.se)
Multiple1
The metabolic risk score (MRS) was calculated using multiple metabolic indicators. (spandidos-publications.com)
Methods1
The user will be able to compare the performances of both methods by using the ROC curves. (xlstat.com)
Model4
One might be able to calculate something like an area (as one proposed answer here does), but it's not clear that would truly represent the area under the ROC curve for the full model. (stackexchange.com)
My initial thoughts were to identify the "correct" number of model classifications and simply divide the number of "correct" observations by the number of total observations to calculate the c-statistic. (stackexchange.com)
The area under the curve was 0.80, indicating a good capability of the model to discriminate between survivors and nonsurvivors. (ajtmh.org)
Contained are functions used to fit a Bayesian multi-environment model (based on the available presets), extract posterior values and maximum posterior values, compute the variance components, check the model's convergence, and calculate the probabilities. (eddelbuettel.com)
Function2
What does coercing the 'direction' argument input in roc function (package pROC in R) do exactly? (stackoverflow.com)
ROC function error 'Predictor must be numeric or ordered. (stackoverflow.com)
Four candidate definitions showed high area under the curve values on ROC testing. (bmj.com)
Single1
A ROC curve with a single point is a worst-case scenario, and any comparison with a continuous classifier will be inaccurate and misleading. (stackexchange.com)
Good1
The ROC curves suggested that there is good correlation between the PMEWS score and the decision to discharge. (bmj.com)
Formula1
What is the formula to calculate the area under the ROC curve from a contingency table? (stackexchange.com)
Variables1
The CMVRA ( 8 ) calculates risk on the basis of ranks of environmental variables for enzootic transmission and is used by health agencies throughout California to measure risk. (cdc.gov)