Definitions
- Sensitivity: probability that a test result will be positive when the disease is present (true positive rate).= a / (a+b)
- Specificity: probability that a test result will be negative when the disease is not present (true negative rate).= d / (c+d)
- Positive likelihood ratio: ratio between the probability of a positive test result given the presence of the disease and the probability of a positive test result given the absence of the disease, i.e.= True positive rate / False positive rate = Sensitivity / (1-Specificity)
- Negative likelihood ratio: ratio between the probability of a negative test result given the presence of the disease and the probability of a negative test result given the absence of the disease, i.e.= False negative rate / True negative rate = (1-Sensitivity) / Specificity
- Positive predictive value: probability that the disease is present when the test is positive.
- Negative predictive value: probability that the disease is not present when the test is negative.
- Accuracy: overall probability that a patient is correctly classified.= Sensitivity × Prevalence + Specificity × (1 − Prevalence)
Published by Dr ATIQUR RAHMAN KHAN
Dr.Atiqur Rahman Khan is a Pediatrician. He is working at Maternity And Children's Hospital, Najran, Saudi Arabia, for more than 15 years, which gives him great inner satisfaction. He has successfully faced the most challenging cases, especially since my work involves little lives on a large scale, from chronic disorder to common childhood health issues. He has experience treating both inpatient and outpatient children and looking after prematurely born babies in a NICU. He believes in taking his work seriously as he understands the implication of having a child's future in his hands.
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