ROC_value: Calculate TPR and FPR at Each Probability Threshold

In bmcguir8/mcguiR: Quick Plotting to Compare Regression Models

Description

Only supports binary logistic regression at this time

Usage

ROC_value(model, data, ind_column, success, failure, na.rm = T)

Arguments

model	regression model to be used
data	training/testing data to use with model, MUST include all predictors in model
ind_column	independent (outcome) variable column in dataset - please use data$column syntax
success	character vector; how 'success' is coded in data
failure	character vector; how 'failure' is coded in data
na.rm	when T, only returns probability thresholds that have values for both 'TPR' and 'FPR' values

Value

data frame with TPR, FPR and Probability Threshold columns

Examples

## Not run: 
iris2 <- iris[stringr::str_detect(Species, "setosa", negate = T), ]
irismodel <- glm(Species ~ ., data = iris2, family = binomial)
roc_value <- ROC_value(irismodel, iris2, iris2$Species, "virginica",
"versicolor")
## End(Not run)

bmcguir8/mcguiR documentation built on Jan. 7, 2021, 8:40 p.m.