A function to get a decision (modus) from a vector of classes

decision_modus is a function that can be used to find the most frequent (modus) decision. The classes can be defined by the user (e.g., a", "n", "y" -> "ambiguous", "negative", "positive"). This function is useful if large collections of varying decision (e.g., "a", "a", "a", "n", "n") need to be condensed to a single decision (3 x "a", 2 x "n" -> "a").

decision_modus(data, variables = c("a", "n", "y"), max_freq = TRUE)

Arguments

data	is a table containing the classes.
variables	is the class to look for.
max_freq	is a logical parameter (default == TRUE) delivers either the most occurring class or a summary.

Examples

# First example
# Enter a string of arbritary of "a","a","y","n"
# Result:
# [1] a
# Levels: a b n y

decision_modus(c("a","a","y","n","b"))
#> [1] a
#> Levels: a b n y

# Second example
# Analyze data from the decision_res_testdat.csv data file
filename <- system.file("decision_res_testdat.csv", package = "PCRedux")
my_data <- read.csv(filename)
head(my_data)
#>   testdat test.result.1 test.result.2 test.result.3 conformity
#> 1    F1.1             y             y             y       TRUE
#> 2    F1.2             y             y             y       TRUE
#> 3    F1.3             n             n             n       TRUE
#> 4    F1.4             n             n             n       TRUE
#> 5    F2.1             y             y             y       TRUE
#> 6    F2.2             y             y             y       TRUE

dec <- unlist(lapply(1L:nrow(my_data), function(i) {
       decision_modus(my_data[i, 2:4])
}))

names(dec) <- my_data[, 1]
dec
#> F1.1 F1.2 F1.3 F1.4 F2.1 F2.2 F2.3 F2.4 F3.1 F3.2 F3.3 F3.4 F4.1 F4.2 F4.3 F4.4 
#>    y    y    n    n    y    y    n    n    y    y    n    n    y    y    n    n 
#> F5.1 F5.2 F5.3 F5.4 F6.1 F6.2 F6.3 F6.4 
#>    y    y    n    n    y    y    n    n 
#> Levels: y n