DataCheck5 {InterVA5}

Data cleaning for InterVA-5 algorithm

Description

This function implements the data cleaning steps in the InterVA5 software.

Usage

DataCheck5(Input, id, probbaseV5, InSilico_check = FALSE, write)

Arguments

Input

original data vector for one observation coded by 0 (absence), 1 (presence), and NA (missing).

id

id for this observation

probbaseV5

matrix of probbaseV5

InSilico_check

logical indicator for if the check uses InSilicoVA rule. InSilicoVA rule sets all symptoms that should not be asked to missing. In contrast, the default InterVA5 rule sets these symptoms to missing only when they take the substantive value.

write

logical indicator of writing to file

Value

Output

new data vector

firstPass

message for the first pass check

secondPass

message for the second pass check

Author(s)

Jason Thomas, Zehang Li, Tyler McCormick, Sam Clark

References

http://www.interva.net/

See Also

InterVA5.plot

Examples

data(RandomVA5)
data(probbaseV5)
probbaseV5 <- as.matrix(probbaseV5)
RandomVA5 <- as.matrix(RandomVA5)
input <- as.character(RandomVA5[1, ])
input[which(toupper(input) == "N")] <- "0" 
input[which(toupper(input) == "Y")] <- "1" 
input[which(input != "1" & input != "0")] <- NA
input <- as.numeric(input)
output <- DataCheck5(Input=input, id="d1", probbaseV5=probbaseV5, write=TRUE)