This presentation is about basic explanation of various statistical analysis

1. Q. What is Sensitivity, Specificity, positive and negative
predictive values of a test? How they are calculated?
SGRH

2. • Intrinsic characteristics of a test:
Sensitivity
Specificity
• Performance of a test in a population:
Predictive value of a positive test
Predictive value of a negative test
SGRH

3. Sensitivity
Sensitivity = True positives / Affected persons
Persons testing positive
(True positives)
Persons testing negative
(False negatives)
Affected persons
(Positive by gold standard)
Ability of the test to identify correctly affected individuals
Proportion of persons testing positive among affected
individuals
SGRH

4. • Factors influencing the sensitivity of a test:
Characteristics of the affected persons
• Not affected by prevalence of the disease
• The greater the test’s sensitivity, the lower the false-negative
rate
• If a test has high sensitivity then a negative result would suggest
the absence of disease.
SGRH

5. Specificity
Specificity = True negatives / Non-affected persons
Persons testing negative
(True negatives)
Persons testing positive
(False positives)
Non-affected persons
(Negative by gold standard)
Ability of the test to identify correctly non-affected individuals
Proportion of person testing negative among non affected
individuals
SGRH

6. • Factors influencing specificity of a test:
Characteristics of the non-affected persons
• Not affected by prevalence of the disease
• The greater the test’s specificity, the lower the false-positive rate
• If a test has high specificity, a positive result from the test
means a high probability of the presence of disease
SGRH

7. Predictive value of a positive test
Persons affected
(True positives)
Persons not affected
(False positives)
Persons testing positive
(Positive by test)
Predictive value of a positive test = True positives/Persons testing positive
Probability that an individual testing positive is truly affected
Proportion of affected persons among those testing positive
SGRH

8. Predictive value of a positive test
Status of persons
Affected Non-
Effected
Test
Positive A B A+B
Negative C D C+D
A + C B+D A+C+B+D
PVP = A / (A+B)
SGRH

9. • Factors influencing the predictive value positive of a test:
a) Specificity: The more the test is specific, the more it will
be negative for non affected persons
Thus, when the test is positive, it is probably
truly positive
b) Prevalence of the disease:
Low prevalence: Test will pick up more false positives
High prevalence: Test will pick up more true positives
SGRH

10. Predictive value of a negative test
Persons non affected
(True negatives)
Persons affected
(False negatives)
Persons testing negative
(Negative by test)
Predictive value of a negative test =True negatives/Persons testing negative
The predictive value of a negative test is the probability that an
individual testing negative is truly non-affected
Proportion of non-affected persons among those testing negative
SGRH

11. Predictive value of a negative test
Status of persons
Affected Non-
affected
Test
Positive A B A+B
Negative C D C+D
A + C B+D A+C+B+D
PVN = D / (C+D)
SGRH

12. • Factors influencing the predictive value negative of a test:
a) Sensitivity: The more the test is sensitive, the more it
captures affected persons.
Thus, when the test is negative, it is probably
truly negative
b) Prevalence of the disease:
Low prevalence: Test will pick up more true negatives
High prevalence: Test will pick up more false negatives
SGRH