Description Usage Arguments Examples
View source: R/roc_selection.R
This function takes a dataframe and performs a series of calcuations in a step-wise fashion according to a maximum, minimum, and step numbers of bins. The "optimal" number of bins for a type-2 ROC calcuation.
1 | roc_selection(data, varname, outcomevar, low_bin, high_bin, step_bin)
|
data |
a dataframe that holds the judgment and outcome variables. |
varname |
the name of the variable that is to be binned. |
outcomevar |
the name of the outcome variable that the hit and false alarm bin calculations are based on. |
low_bin |
a positive integer indicating the lowest number of bins for the calculations. |
high_bin |
a positive integer indicating the highest number of bins for the calculations. |
step_bin |
a positive integer indicating the step-wise progression through bin numbers. |
1 2 3 4 5 6 7 8 9 10 11 12 13 | # Randomly select 100 integers from 0 - 100.
set.seed(2)
a <- sample(0:100,100,replace=TRUE)
# Randomly select 100 integers of 0 or 1.
set.seed(2)
b <- sample(0:1,100,replace=TRUE)
# Send to data frame.
c <- data.frame(a,b)
# Send to function; output bins + calculations
roc_selection(c, varname = "a", outcomevar = "b", 2, 10, 1)
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