Combine Medical Decision Tests

Function for combining multiple Medical Decision Tests and evaluating their performance. Calculate sensitivity, specificity, positive predictive value, negative predictive value for combined tests using different combination rules.

Usage

decisioncombine(
  data,
  gold,
  goldPositive,
  test1,
  test1Positive,
  test2,
  test2Positive,
  test3,
  test3Positive,
  combRule = "any",
  pp = FALSE,
  pprob = 0.3,
  od = FALSE,
  fnote = FALSE,
  ci = FALSE,
  fagan = FALSE,
  showIndividual = TRUE
)

Arguments

data

The data as a data frame.

gold

.

goldPositive

.

test1

.

test1Positive

.

test2

.

test2Positive

.

test3

.

test3Positive

.

combRule

Rule for combining test results. "any" means positive if any test is positive (OR), "all" means positive only if all tests are positive (AND), and "majority" means positive if more than half of tests are positive.

pp

.

pprob

Prior probability (disease prevalence in the community). Requires a value between 0.001 and 0.999, default 0.300.

od

Boolean selection whether to show frequency tables. Default is 'false'.

fnote

.

ci

.

fagan

.

showIndividual

.

Value

A results object containing:

results$text1					a preformatted
results$text2					a html
results$cTable					a table
results$indTable1					a table
results$indTable2					a table
results$indTable3					a table
results$nTable					a table
results$ratioTable					a table
results$epirTable_ratio					a table
results$epirTable_number					a table
results$plot1					an image

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$cTable$asDF

as.data.frame(results$cTable)

Examples

# \donttest{
# example will be added
# }