Estimate sensitivity, specificity, positive predictive value, negative predictive value and prevalence from data in the 2 x 2 table for an infectious disease and its diagnostic test. The image presents a table and a question regarding specificity on an educational topic. Here's the detailed transcription:### Table: Test Results and Disease Status| Status | Disease Present | Disease Absent | Marginal Total ||-----------------------|-----------------|----------------|----------------|| Test Positive | 57 | 4 | 61 || Test Negative | 43 | 96 | 139 || Marginal Total | 100 | 100 | 200 |### Question2. SpecificityOptions:- ○ 57%- ○ 93%- ○ 69%- ○ 96%- ○ 50%### ExplanationIn the context of this table, specificity refers to the ability of the test to correctly identify those without the disease (Disease Absent). It is calculated using the formula:\[\text{Specificity} = \left(\frac{\text{True Negatives}}{\text{True Negatives} + \text{False Positives}}\right) \times 100\]From the table:- True Negatives = 96- False Positives = 4Using the formula:\[\text{Specificity} = \left(\frac{96}{96 + 4}\right) \times 100 = 96\%\]

Specificity: It is the percentage of healthy people who tested negative by the total number of…

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stimate sensitivity, specificity, positive predictive value, negative predictive value and prevalence from data in the 2 x 2 table for an infectious disease and its diagnostic test.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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