sensitivity is about thinking true or false?
Answers
Explanation:
Sensitivity is the ability of a test to correctly identify those patients with the disease. It is also known as the True Positive Rate (TPR), i.e. the percentage of sick persons who are correctly identified as having the condition. Therefore sensitivity is the extent to which actual positives are not overlooked.
Answer:
These are terms that are fundamental to understanding the utility of clinical tests. They are the most essential variables when designing diagnostic tests, in determining how reliable the tests are and also how reliable the results obtained from the results are. When using known samples of a disease, sensitivity and specificity variables can be calculated for evaluation of the test and its results.
Sensitivity and specificity are independent of the population of interest subject to the tests while Positive predictive value (PPV) and negative predictive value (NPV) is used when considering the value of a test to a clinician and are dependent on the prevalence of the disease in the population of interest.
The positive predictive value (PPV) is the probability that a subject/sample that returns a positive result really is positive and the negative predictive value (NPV) is the probability that a subject/sample that returns a negative result really is negative
To evaluate a diagnostic test, it is very important to calculate its sensitivity and specificity in order to determine its effectiveness.
Positive and Negative terms do not refer to the value of the condition of interest but the presence or absence of the condition. The condition could be a disease, therefore positive means diseased and negative means healthy.
What is Sensitivity, Specificity, False positive, False negative