epiR (version 0.9-18)

epi.nomogram: Post-test probability of disease given sensitivity and specificity of a test

Description

Computes the post-test probability of disease given sensitivity and specificity of a test.

Usage

epi.nomogram(se, sp, pre.pos, verbose = FALSE)

Arguments

se

test sensitivity (0 - 1).

sp

test specificity (0 - 1).

pre.pos

the pre-test probability of disease in the patient.

verbose

logical, indicating whether detailed or summary results are to be returned.

Value

• A list containing the following:
• likelihood.ratio
  the likelihood ratio of a positive and negative test.
• prob
  the post-test probability of disease given a positive and negative test.

References

Hunink M, Glasziou P (2001). Decision Making in Health and Medicine - Integrating Evidence and Values. Cambridge University Press, pp. 128 - 156.

Examples

## You are presented with a dog with lethargy, exercise intolerance, 
## weight gain and bilaterally symmetric truncal alopecia. You are 
## suspicious of hypothyroidism and take a blood sample to measure 
## basal serum thyroxine (T4).

## You believe that around 5\% of dogs presented to your clinic with 
## a signalment of general debility have hypothyroidism. The serum T4 
## has a sensitivity of 0.89 and specificity of 0.85 for diagnosing 
## hypothyroidism in the dog. The laboratory reports a serum T4 
## concentration of 22.0 nmol/L (reference range 19.0 to 58.0 nmol/L). 
## What is the post-test probability that this dog is hypothyroid?

epi.nomogram(se = 0.89, sp = 0.85, pre.pos = 0.05, verbose = FALSE)

## The post-test probability that this dog is hypothyroid is 24\%.