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

Statistical analysis definitions

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Page 1: Statistical analysis definitions

Q. What is Sensitivity, Specificity, positive and negative

predictive values of a test? How they are calculated?

SGRH

Page 2: Statistical analysis definitions

• 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

Page 3: Statistical analysis definitions

Sensitivity

Sensitivity = True positives / Affected persons

Persons testing positive(True positives)

Persons testing negative(False negatives)

A ffected persons(Positive by gold standard )

Ability of the test to identify correctly affected individuals

Proportion of persons testing positive among affected individuals

SGRH

Page 4: Statistical analysis definitions

• 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

Page 5: Statistical analysis definitions

Specificity

Specificity = True negatives / Non-affected persons

Persons testing negative(True negatives)

Persons testing positive(False positives)

N on-affected persons(N egative by gold standard )

Ability of the test to identify correctly non-affected individuals

Proportion of person testing negative among non affected individuals

SGRH

Page 6: Statistical analysis definitions

• 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

Page 7: Statistical analysis definitions

Predictive value of a positive test

Persons affected(True positives)

Persons not a ffected(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

Page 8: Statistical analysis definitions

Predictive value of a positive test

Status of persons

Affected Non-Effected

TestPositive A B A+B

Negative C D C+D

A + C B+D A+C+B+D

PVP = A / (A+B)

SGRH

Page 9: Statistical analysis definitions

• 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

Page 10: Statistical analysis definitions

Predictive value of a negative test

Persons non affected(True negatives)

Persons affected(False negatives)

Persons testing negative(N egative 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

Page 11: Statistical analysis definitions

Predictive value of a negative test

Status of persons

Affected Non-affected

TestPositive A B A+B

Negative C D C+D

A + C B+D A+C+B+D

PVN = D / (C+D)

SGRH

Page 12: Statistical analysis definitions

• 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