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psychopdaROC Perfect Separation Data

Source: R/data_psychopdaROC_docs.R
psychopdaROC_perfect.Rd

Dataset with 100 patients showing perfect discrimination between positive and negative cases (AUC = 1.0), useful for testing edge case handling.

Usage

psychopdaROC_perfect

Format

A data frame with 100 rows and 3 variables:

patient_id

Character: Patient identifier (PT001-PT100)

condition

Factor: "Positive" or "Negative" (50%/50% prevalence)

perfect_test

Numeric: Test values (80-100 for positive, 0-20 for negative)

Source

Generated test data for ClinicoPath package

Details

Complete separation between classes with no overlap. Positive cases have values uniformly distributed between 80-100, negative cases between 0-20. Tests ability to handle perfect discrimination scenarios.

Examples

data(psychopdaROC_perfect)
psychopdaROC(data = psychopdaROC_perfect, dependentVars = "perfect_test",
             classVar = "condition", positiveClass = "Positive")
#> Error in psychopdaROC(data = psychopdaROC_perfect, dependentVars = "perfect_test",     classVar = "condition", positiveClass = "Positive"): argument "refVar" is missing, with no default