README.md

In overdodactyl/diagnosticSummary: Diagnostic Summaries

diagnosticSummary

diagnosticSummary is designed to quickly create diagnostic summaries and reports for binary classification data.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("overdodactyl/diagnosticSummary")

Example

library(diagnosticSummary)
# Load sample data
data("dx_heart_failure")
head(dx_heart_failure)
#>   AgeGroup    Sex truth   predicted           AgeSex
#> 1  (20,50]   Male     0 0.016164112   (20,50] - Male
#> 2  (20,50]   Male     0 0.074193671   (20,50] - Male
#> 3  (20,50] Female     0 0.004677979 (20,50] - Female
#> 4  (20,50] Female     0 0.017567313 (20,50] - Female
#> 5  (20,50] Female     0 0.017517025 (20,50] - Female
#> 6  (20,50]   Male     0 0.051570734   (20,50] - Male

# Create dx object
dx_obj <- dx(
  data = dx_heart_failure,
  true_varname = "truth",
  pred_varname = "predicted",
  outcome_label = "Heart Attack",
  threshold_range = c(.1,.2,.3),
  setthreshold = .3,
  doboot = TRUE,
  bootreps = 1000,
  grouping_variables = c("AgeGroup", "Sex", "AgeSex")
)

summary(dx_obj, variable = "Overall", show_var = F, show_label = F)

| measure | summary | |:---------------------------------|:---------------------| | AUC ROC | 0.904 (0.864, 0.943) | | Accuracy | 79.3% (73.9%, 84.1%) | | Sensitivity | 84.7% (76.0%, 91.2%) | | Specificity | 76.1% (68.8%, 82.4%) | | Positive Predictive Value | 68.0% (59.0%, 76.2%) | | Negative Predictive Value | 89.2% (82.8%, 93.8%) | | LRT+ | 3.54 (2.66, 4.71) | | LRT- | 0.20 (0.13, 0.32) | | Odds Ratio | 17.59 (9.12, 33.94) | | F1 Score | 75.5% (68.3%, 81.5%) | | F2 Score | 80.7% (74.0%, 86.4%) | | Prevalence | 37.5% (31.7%, 43.7%) | | False Negative Rate | 15.3% (8.8%, 24.0%) | | False Positive Rate | 23.9% (17.6%, 31.2%) | | False Discovery Rate | 32.0% (23.8%, 41.0%) | | AUC PR | 0.87 | | Cohen’s Kappa | 0.58 (0.48, 0.68) | | Matthews Correlation Coefficient | 59.0% (48.9%, 68.4%) | | Balanced Accuracy | 80.4% (75.3%, 85.1%) | | Informedness | 60.8% (50.9%, 70.7%) | | Markedness | 57.2% (47.4%, 67.2%) | | G-mean | 80.3% (75.1%, 84.8%) | | Fowlkes-Mallows Index | 75.9% (69.6%, 81.4%) | | Brier Score | 0.11 | | Pearson’s Chi-squared | p\<0.01 | | Pearson’s Chi-squared | p\<0.01 | | Fisher’s Exact | p\<0.01 | | G-Test | p\<0.01 |

Threshold= 0.3

overdodactyl/diagnosticSummary documentation built on Jan. 28, 2024, 10:07 a.m.