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Questions tagged [sensitivity-specificity]

Sensitivity & specificity are descriptive statistics that measure the quality of a classification system. They are the proportion of real positives that are classified correctly (sensitivity) & the proportion of real negatives that are classified correctly (specificity). They are an integral part of ROC analysis.

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Deriving a loss function properly accounting for different error type costs

Consider a classification setting like a medical test: Not finding an existing health issue might be much worse (by a factor of 50) than assuming an issue when there is none. I.e. a setting in which ...
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ROC curve looking off compared to my results

I have a dependent variable "response" as binary 1 = response, 0 = no response (for surgery). I have an independent variable of a certain measurement in degrees (continuous/ordered variable). A ...
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FPR in Confusion Matrix

I was trying to manually calculate $\text{TPR}$ and $\text{FPR}$ for the given data. But unfortunately I dont have any false positive cases in my dataset and even no true positive cases. So I am ...
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Why is the mean of sensitivity and specificity equal to the AUC?

For a given cut-point in a prediction model or score, the mean of sensitivity and specificity equals the AUC. I've read that and I have observed this empirically. How can I prove this?
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How to Rank Parameters using Sobol Indices (Variance-based Ranking)

I am trying to compare different parameter ranking methods. The Sobol Indice method is the most representative method for ranking significant parameters based on contribution to output variance, ...
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What would be the True Negatives (TN) and FPR in this case?

I've developed an algorithm that detects shapes in a given image. The input is an image with a triangle, a square and a circle. My algorithm outputs triangle, square, pentagon. If I'm not mistaken, ...
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How to back out individual confusion matrix values from scalar measures like sensitivity and specificity?

Consider a standard 2X2 Binary Classification Matrix: TP | FP FN | TN From which we can derive sensitivity and specificity, and other measures. Now, let's assume we have ONLY output measures: ...
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How to make sense of both high FNR and NPV?

So, even though this is one of the most basic and already explained things about statistics I always seem to find way not to get it. Having this table which shows high Negative Predictive Value (352/...
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Finding optimal cutoff point [duplicate]

.Hello,everyone. I am studying the influence of one biomarker on multiple disease characteristics, and I would like to calculate its cutoff point. I created univariate ROC curves to investigate the ...
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Rule of Thumb for Sensitivity and Specificity

What are rule of thumb cutoffs for sensitivity and specificity? What is high, good, fair, low?
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17 views

Combining time series to increase sensitivity

I have two sensors logging data synchronously. The two sensors are similar, so the recorded time series are correlated except for some special conditions. I recorded data in different input parameter ...
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55 views

How to decide threshold values for AUC?

With respect to the pROC package for R(https://rdrr.io/cran/pROC/man/ggroc.html). ...
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Calculate AUC using sensitivity and specificity values only

How to calculate AUC, if I have values of sensitivity and specificity for various threshold cutoffs? I have sensitivity and specificity values for 100 thresholds. ...
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Samle size calculation for paired comparative diagnostic accuracy study

I would like to estimate an appropriate sample size for a medical imaging study. I prefer to use R. A standard thest testS will be compared to a modified standard ...
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Finding PCA-like directions in feature space that maximise sensitivity to a target variable

I have a fairly large space of feature variables in which I want to build a predictor for a target variable. My input dataset for training the predictor are sampled from the space using a mix of log ...
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Sensitivity rates where TP =0 and FN =0

In calculating sensitivity rates where TP =0 and FN =0 and the formula is TP/(TP+FN) - although it mathematically won't compute, does this equate to 100% sensitivity since it has correctly identified ...
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Correct calculation of repeated cross-validation classification metrics

We can obtain a resampled estimate of training set classification accuracy from caret::confusionMatrix.train(model) e.g., ...
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Can positive and negative likelihood ratios be combined into one parameter?

Positive and negative likelihood ratios (PLR, NLR) are considered to be much better than sensitivity and specificity as parameters of usefulness of a test. Is it possible to combine PLR and NLR into ...
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Acceptable Accuracy, Precision, Sensitivity, and Specificity Thresholds [duplicate]

Are there general rule of thumbs for acceptable accuracy, precision, sensitivity, and specificity values/thresholds in classification? I would imagine that this depends on different applications. I ...
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Why are likelihood ratios weighted for prevalence?

I notice LLR's are weighted for prevalence if the prevalence differs from 0.5 (see: http://vassarstats.net/clin2.html) Can someone explain why this is? I'm a medical student, not a statistician, so I'...
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Can I estimate a new post-test probability?

Let's say a patient, let's assume a pre-test probability of 20%, gets a test done with a positive predictive value of 70%. He tests positive. He gets another test done, which has a positive predictive ...
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Is this test muddying the water?

In the case of a neurological disease called idiopathic normal pressure hydrocephalus, if the patient is suspected positive for the condition, they are administered a test called the spinal tap test. ...
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What is the correct definition of Selectivity : TPR or TNR ? Since contradictory literature exists

The reason of my question is because contradictory articles exist. Talking about the confusion matrix's performance metrics, we can find: English wikipedia pages mention that ...
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1answer
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Plot of Probability of Cancer vs Test Sensitivity

I'm looking at the following problem and its solution and am really struggling to understand how they came up with the necessary values. My Questions 1, For part (a) we are asked to plot $y=P(C|+)$...
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Compute Sensitivity and Specificity with Incomplete Data

I have two data sets $A$ and $B$ which I want to combine using statistical methods (e.g. some matching algorithms such as Nearest Neighbor). I have a third data set $C$ that encompasses the true ...
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Assess sensitivity of a binary screening result across other continuous covariate(s)

I want to assess the sensitivity of a diagnostic screening test, which is a binary test (screen +ve and screen -ve). There is no continuous measure from this test - it is literally yes or no. My ...
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estimate probability that sensitivity/specificity greater than threshold value

Is there a Bayesian method to estimate the probability that the sensitivity of a diagnostic test is greater than some value, say 0.70? Rather than estimate sensitivity and a confidence interval (e.g., ...
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Calculation of accuracy (and Cohen's kappa) using sensitivity, specificity, positive and negative predictive values

I read How to calculate specificity from accuracy and sensitivity, but I have two diagnostic performance measures more. Please correct me if I am wrong: if Sensitivity=TP/(TP+FN) Specificity=TN/(TN+...
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Sensitivity and specificity on cases rather than individual days

I have data collected from sensors to detect disease in several individuals. Each individual has a known disease status (labelled Actual in the table below) for ...
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380 views

If the position of 0 1 in confusion matrix changes does the formula for sensitivity changes

It may sounds very silly question, but I want to clear myself In confusion matrix we normally takes values like below: ...
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Do you need to calculate sample size to evaluate a new diagnostic test?

I am writing a grant application which will be evaluating a new diagnostic test. The test will predict whether a patient with lung fibrosis will remain stable or progress. I am using an existing ...
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302 views

Is it possible for a model to have higher sensitivity/specificity but lower accuracy and AUC?

In the evaluation of classification models, I've found one model to have a higher accuracy and c-statistic (AUC) as compared to a second model. However, the second model has higher sensitivity, ...
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232 views

Sensitivity & Specificity calculation

I have a medical diagnostic test $A$ and test $B$. Test $B$ is the current gold standard. Test $A$ has an excellent negative predictive value and if it is negative, test $B$ is not performed as it is ...
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242 views

Is it possible to get high sensitivity but low precision

Consider a case where the number of labelled data as 0 = 1400 and labelled as 1 =100. This dataset is imbalanced with a majority examples belonging to normal class (0) and minority being class labeled ...
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Educational purpose :Calculation of sensitivity and specificity from confusion matrix for this example

Consider a case where the number of labelled data as 0 = 1400 and labelled as 1 =100. The data labelled as 0 denote normal operating conditions and data labelled as ...
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Statistical significance (p-value) for comparing two classifiers with respect to (mean) ROC AUC, sensitivity and specificity

I have a test set of 100 cases and two classifiers. I generated predictions and computed ROC AUC, sensitivity and specificity for both classifiers. Question 1: How can I compute p-value to check if ...
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how to calculate the specificity, sensitivity and accuracy from the 4 factors

Used decision tree method. Created treemodel for the combined datasets and tried to make prediction on test datasets to calculate error. Please help me on how to calculate the specificity, sensitivity ...
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How to tell the likelihood of getting a false positive? [closed]

Say we have a test for a disease we are comparing with the gold standard. You are given the prevalence of the disease, which is 1%, and sensitivity, 80%, and specificity, 90% and a total population of ...
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55 views

Why do dummy regressors decrease sensitivity in linear regression?

For linear regression analysis, I thought that the addition of covariates which are not related to the dependent variable $Y$ does not decrease sensitivity. Such random/dummy regressors can be ...
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435 views

Is the sum of p-value and specificity 1

When I look at the definition of p value carefully: $$ p = Pr(X<x|H_0) $$ where $H_0$ means the null hypothesis is true, thus condition negative. That having a test statistic $X<x$ means ...
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299 views

What is a good value for Sensitivity and specificity of a predictive model?

Hope all is well. I developed predictive models and I wonder if anyone has some gold standard for sensitivity and specificity from the literature so that I can refer my results to the ones in the ...
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259 views

Average of Precision and True negative rate as an accuracy metric

When attempting to construct a classifier for a somewhat imbalanced data set, I was led to the question of measuring the performance of the classifier. One of the first things I thought of was to take ...
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289 views

Applying SMOTE and increasing sensitivity

I am trying to analyze lending club data and want to predict whether a loan is risky or safe using random forest with decision tree as a classifier. The data is imbalanced. It contains one-fourth of ...
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1k views

Determine baseline for a machine learning project

I work with a unbalanced data set (it is about people who actually bought stuff): Bought stuff: Yes ~ 3% Bought stuff: NO ~97% The most important task for my ...
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528 views

Harmonic mean of precision, recall and specificity

I have a system whose performance was characterized in terms of the amount of true positives (TP), true negatives (TN), false positives (FP) and false negatives (FN). There is a rate that summarizes ...
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Compare cut-offs with respect to sensitivity etc

I have a score and a dichotomous criterion for n observations. Using a ROC-Analysis, I found some optimal cut-off, say c. Now, literature (e.g., author of scale with which the score was determined) ...
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Is sensitivity or specificity a function of prevalence?

Standard teaching says that sensitivity and specificity are properties of the test and are independent of prevalence. But isn't this just an assumption? Harrison's principles of internal medicine ...
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Assessing correlated predictions

Let's assume we have a prediction algorithm (if it helps, imagine it's using some boosted tree method) that does daily predictions for whether some event will happen to a unit (e.g. a machine that ...
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58 views

What is the variance of negative predictive value when sensitivity is 1?

Variance of NPV is calculated using (1-sensitivity). If estimated( sensitivity) =1 then var(NPV)=0 Is there an alternative formula for var(NPV) similar to Score formula for sensitivity?
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Generalized Sensitivity and Specificity

I'm interested in notation and terminology regarding performance measures related to Sensitivity (SEN) and Specificity (SPC). These two measures are commonly used in binary classification problems. I'...