False Negative Rate Calculator
Uses prevalence and sensitivity to determine the false negative and true positive values.
Read more about the statistical measures and the formulas used during clinical studies, in the text below the tool.
The false negative rate calculator determines the rate of incorrectly identified tests based on prevalence and specificity.
The result provided consists in the false negative and true positive values, the pre-test odds and the false negative rate.
The formulas used are included in the table below:
| Concept | Formula |
| False Negative | (1 - Sensitivity) x Prevalence |
| True Positive | Sensitivity x Prevalence |
| Pre Test Odds | Prevalence / (1 - Prevalence) |
| False Negative Rate | 100 x False Negative / (True Positive + False Negative) |
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Steps on how to print your input & results:
1. Fill in the calculator/tool with your values and/or your answer choices and press Calculate.
2. Then you can click on the Print button to open a PDF in a separate window with the inputs and results. You can further save the PDF or print it.
Please note that once you have closed the PDF you need to click on the Calculate button before you try opening it again, otherwise the input and/or results may not appear in the pdf.
Variables and formulas
The above calculator is based on prevalence and sensitivity values which can be input in % (0 to 100%), fraction or ratio (between 0 and 1).
Prevalence of disease is a statistical concept that refers to the disease cases (in number, percentage or ratio) present in a population, during a study or at a given time.
It is only logical that prevalence is influenced by the population dimension.
Sensitivity or the true positive rate is the probability that a test will result positive (indicate disease) amongst the subject with the disease. This is also a measure of the avoidance of false negatives.
Sensitivity = True Positive / (True Positive + False Negative) x 100
There are four results provided by the calculator:
■ False Negative: disease subjects incorrectly identified as non disease.
■ True Positive: disease subjects correctly identified as disease.
■ Pre-Test Odds: the subjective probability of the presence of a condition (Disease), before the diagnostic test.
■ False Negative Rate: rate of incorrectly identified as non disease out of total disease.
The relationship between the above statistical concepts is explained below:
| Test result | Disease | Non Disease | Total Number |
| Positive | True Positive | False Positive | Total Test Positive |
| Negative | False Negative | True Negative | Total Test Negative |
| Total Disease | Total Non Disease | Total |
The 4 formulas used in the above calculator are:
| Concept | Formula |
| False Negative | (1 - Sensitivity) x Prevalence |
| True Positive | Sensitivity x Prevalence |
| Pre Test Odds | Prevalence / (1 - Prevalence) |
| False Negative Rate | 100 x False Negative / (True Positive + False Negative) |
References
1. Lalkhen AG, McCluskye A. (2008) Clinical tests: sensitivity and specificity. Contin Educ Anaesth Crit Care Pain. 2008; 8(6): 221-223.
2. Griner PF, Mayewski RJ, Mushlin AI, Greenland P. Selection and interpretation of diagnostic tests and procedures. Principles and applications. Ann Intern Med. 1981; 94(4 Pt 2):557-92.
Specialty: Research
Objective: Determination
Type: Calculator
No. Of Variables: 2
Article By: Denise Nedea
Published On: May 29, 2017 · 09:33 AM
Last Checked: May 29, 2017
Next Review: May 29, 2023