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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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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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GLMM with rare events causing issues with specificity?

I have run a generalized linear mixed model (link=logit) and my outcome of interest is present in about 8% of observations. The total sample is 1,717,323 and of these 131,389 observations are where ...
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27 views

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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1answer
157 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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199 views

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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84 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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89 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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117 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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170 views

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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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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Effects of high variance of parameters of a function

Suppose I have some function $f$ (e.g. convolution) with parameters $\theta$, some input $X$ (e.g. image), and a perturbed input $\tilde X$ which is defined as $\tilde X = X + \epsilon$. What ...
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How to test for significant difference between two classification tests

I want to predict the disease status (sick/healthy) of a group of patients using two classification methods. And I want to test if there is a significant difference in how well they perform; i.e. are ...
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254 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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1answer
202 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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1answer
186 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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184 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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2answers
676 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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1answer
378 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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24 views

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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748 views

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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108 views

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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39 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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224 views

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'...
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1answer
4k views

What is AUC (Area Under the Curve)?

I've seen many questions posted about AUC but I'm still struggling to understand. I see this definition for AUC everywhere "The AUC is an estimate of the probability that a classifier will rank a ...
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1answer
249 views

How to determine a sample size

Given that I have an algorithm that classifies data points as 'true' or 'false'. and I want to estimate its FPR, FNR. It is not a supervised model where I start with a large training set of labeled ...
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how to find sensitivity and specificity for more than two levels in the dependent variable from the confusion matrix?

For the above confusion matrix how to compute the sensitivity and specificity manually. I cann't able to understand when the dependent variable has more than two levels
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574 views

95% confidence intervals of sensitivity and specificity exceeding 100%. How is it possible?

I read this abstract (unfortunately, I have no access to the full text): https://doi.org/10.1136/bmj.318.7177.193b. How is it possible for 95% confidence intervals of sensitivity and specificity to ...
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176 views

How to simulate the distribution of a diagnostic test

I have a parameter described as mean (95% CI low-hi) and would like to build a distribution that will have approximately that mean and lower/upper bounds. The ...
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37 views

What is the correct method for comparing sensitivity and specifity of different tests?

What is the correct method of comparing efficiency of different test for one sample of individuals? Are ROC and AUC enough? Comparing of sensitivity and specifity values of the tests with McNemar ...
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27 views

How to evaluate sensitivity and specifity of different tests

I am comparing two test using different cut-off values with golden standart test . How is it to be reported. Is it sufficent to report sensitivity, specivity, PPV and NPV with 95 CI or should I ...
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What is the usefulness of detection rate in a confusion matrix?

In the R caret documentation for confusionMatrix(): ...
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308 views

Calculating sensitivity and specificity from survival data

I have a diagnostic test performed on 100 participants at baseline. I then follow up these participants for variable periods of time and have data regarding survival. I have used a Cox regression ...
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1answer
242 views

Sensitivity/Specificity compared to Area Under Curve as measure of Screen Accuracy

In relation to the disorder I'm studying Screen A is reported as having a sensitivity of 90% and a specificity of 89%. Screen B is reported as having a AUC of .79 with no other data provided. Could ...
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565 views

Is very high specificity and very low sensitivity attributable to mismatched class sizes?

I've generated a gradient boosting model using r-caret on data which I expect to have little to no predictive value. Class distribution is heavily skewed with ~15000 negative and ~1000 positive. Caret'...
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1answer
1k views

Finding True Positive and True Negative values from sensitivity

I have the sensitivity value known as, 91%. Can we derive the True Positive (TP) and True Negative (TN) values from that. Is that possible at all? Thanks.
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372 views

Cost sensitive analysis versus Threshold

I am running a cost sensitive ensemble methods (for the first time to access algorithms of this type) 'CostSensitiveRandomPatchesClassifier' in Python on my imbalanced dataset (positive cases are rare ...
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344 views

what to do when true positive rate is undefined?

I have a binary classification set with about 900 samples. I first use kfold cross validation and AUC of the ROC curve to determine which classifiers perform best. Once I've done that, I use a leave-...