Function for Medical Decision Analysis. Sensitivity, specificity, positive predictive value, negative predictive value.
Usage
decision(
data,
gold,
goldPositive,
newtest,
testPositive,
pp = FALSE,
pprob = 0.3,
od = FALSE,
fnote = FALSE,
ci = FALSE,
fagan = FALSE
)Arguments
- data
The data as a data frame. The data frame should contain the variables specified in the 'variables' option.
- gold
The golden standard variable.
- goldPositive
The positive level of the golden standard variable.
- newtest
The new test variable.
- testPositive
The positive level of the new test variable.
- pp
Boolean selection whether to show prior probability. Default is 'false'.
- 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 table. Default is 'false'.
- fnote
Boolean selection whether to show footnotes. Default is 'false'.
- ci
Boolean selection whether to show 95\ Default is 'false'.
- fagan
Boolean selection whether to show Fagan Nomogram. Default is 'false'.
Value
A results object containing:
results$text1 | a preformatted | ||||
results$text2 | a html | ||||
results$cTable | a table | ||||
results$nTable2 | a preformatted | ||||
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)