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\name{epi.nomogram}
\alias{epi.nomogram}
\title{Post-test probability of disease given sensitivity and specificity of a test}
\description{
Compute the post-test probability of disease given sensitivity and specificity of a test.
}
\usage{
epi.nomogram(se, sp, lr, pre.pos, verbose = FALSE)
}
\arguments{
\item{se}{test sensitivity (0 - 1).}
\item{sp}{test specificity (0 - 1).}
\item{lr}{a vector of length 2 listing the positive and negative likelihood ratio (respectively) of the test. Ignored if \code{se} and \code{sp} are not null.}
\item{pre.pos}{the pre-test probability of the outcome.}
\item{verbose}{logical, indicating whether detailed or summary results are to be returned.}
}
\value{
A list containing the following:
\item{lr}{a data frame listing the likelihood ratio of a positive and negative test.}
\item{prior}{a data frame listing the pre-test probability of being outcome (i.e., disease) positive, as entered by the user.}
\item{post}{a data frame listing: \code{opos.tpos} the post-test probability of being outcome (i.e., disease) positive given a positive test result and \code{opos.tneg} the post-test probability of being outcome (i.e., disease) positive given a negative test result.}
}
\references{
Caraguel C, Vanderstichel R (2013). The two-step Fagan's nomogram: ad hoc interpretation of a diagnostic test result without calculation. Evidence Based Medicine 18: 125 - 128.
Hunink M, Glasziou P (2001). Decision Making in Health and Medicine - Integrating Evidence and Values. Cambridge University Press, pp. 128 - 156.
}
\examples{
## EXAMPLE 1:
## 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, lr = NA, pre.pos = 0.05, verbose = FALSE)
## If the test is positive the post-test probability that this dog is
## hypothyroid is 0.24. If the test is negative the post-test probability
## that this dog is hypothyroid is 0.0068.
## EXAMPLE 2:
## A dog is presented to you with severe pruritis. You suspect sarcoptic
## mange and decide to take a skin scraping (LR+ 9000; LR- 0.1). The scrape
## returns a negative result (no mites are seen). What is the post-test
## probability that your patient has sarcoptic mange? You recall that you
## diagnose around 3 cases of sarcoptic mange per year in a clinic that
## sees approximately 2 -- 3 dogs per week presented with pruritic skin disease.
## Calculate the pre-test probability of sarcoptes:
pre.pos <- 3 / (3 * 52)
## The pre-test probability that this dog is sarcoptes positive is 0.019.
epi.nomogram(se = NA, sp = NA, lr = c(9000, 0.1), pre.pos = pre.pos,
verbose = FALSE)
## If the skin scraping is negative the post-test probability that this dog
## has sarcoptic mange is 0.002.
}
\keyword{univar}% at least one, from doc/KEYWORDS
\keyword{univar}% __ONLY ONE__ keyword per line
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