diagtest {lava} | R Documentation |
Calculate diagnostic tests for 2x2 table
Description
Calculate prevalence, sensitivity, specificity, and positive and negative predictive values
Usage
diagtest(
table,
positive = 2,
exact = FALSE,
p0 = NA,
confint = c("logit", "arcsin", "pseudoscore", "exact"),
...
)
Arguments
table |
Table or (matrix/data.frame with two columns) |
positive |
Switch reference |
exact |
If TRUE exact binomial proportions CI/test will be used |
p0 |
Optional null hypothesis (test prevalenc, sensitivity, ...) |
confint |
Type of confidence limits |
... |
Additional arguments to lower level functions |
Details
Table should be in the format with outcome in columns and test in rows. Data.frame should be with test in the first column and outcome in the second column.
Author(s)
Klaus Holst
Examples
M <- as.table(matrix(c(42,12,
35,28),ncol=2,byrow=TRUE,
dimnames=list(rater=c("no","yes"),gold=c("no","yes"))))
diagtest(M,exact=TRUE)
[Package lava version 1.8.0 Index]