diagtest: Calculate diagnostic tests for 2x2 table

In kkholst/lava: Latent Variable Models

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)

kkholst/lava documentation built on Feb. 22, 2024, 4:07 p.m.