Predictive Values and Likelihood Ratios Given the prevalence of a condition within the population and the sensitivity and specificity of a test designed to indicate the presence of that condition, this page will calculate the predictive values of the test (probabilities for true positive, true negative, false positive, and false negative) and its positive and negative likelihood ratios.

To proceed, enter the known or hypothetical values of prevalence, sensitivity, and specificity into the designated cells, then click the «Calculate» button. To perform a new calculation with a new set of values, click the «Reset» button. All values should be entered as decimal fractions.

Prevalence =			Prevalence, sensitivity, and specificity must each be entered as a proportion.    Calculate         Reset
Sensitivity =
Specificity =

For any particular test result:
probability that it will be positive
probability that it will be negative
For any particular positive test result:
probability that it is a true positive ["positive predictive value"]
probability that it is a false positive
For any particular negative test result:
probability that it is a true negative ["negative predictive value"]
probability that it is a false negative
likelihood Ratios:     [definitions]
Conventional Positive
Conventional Negative
Positive [weighted for prevalence]
Negative [weighted for prevalence]

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©Richard Lowry 2001-
All rights reserved.

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Definitions of likelihood Ratios:
Conventional Positive:

=

conditional probability of positive test result if the condition is present conditional probability of positive test result if the condition is absent

=

sensitivity 1-specificity

Conventional Negative:

=

conditional probability of negative test result if the condition is present conditional probability of negative test result if the condition is absent

=

1-sensitivity specificity

Positive [weighted for prevalence]

=

probability that a positive test result is a true positive probability that a positive test result is a false positive

=

(prevalence)(sensitivity) (1-prevalence)(1-specificity)

Negative [weighted for prevalence]

=

probability of false negative result probability of true negative result

=

(prevalence)(1-sensitivity) (1-prevalence)(specificity)

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