Description
Prediction Model Tools.
Description
Provides additional functions for evaluating predictive models, including plotting calibration curves and model-based Receiver Operating Characteristic (mROC) based on Sadatsafavi et al (2021) <arXiv:2003.00316>.
README.md
Overview
predtools
provides miscellaneous tools for developing and evaluating prediction models.
Table of Contents
- Installation
- Example
- Model-based ROC
- Intercept Adjustment
- Calibration Plot
- Unit Normal Loss Integral in Two Dimensions
Installation
You can install the released version of predtools from CRAN with:
install.packages("predtools")
And the development version from GitHub with:
# install.packages("remotes")
remotes::install_github("resplab/predtools")
Example
The function calibration_plot
takes observed and predicted values from a prediction model and uses ggplot2 to produce a calibration plot:
library(predtools)
library(dplyr)
x <- rnorm(100, 10, 2)
y <- x + rnorm(100,0, 1)
data <- tibble(x,y)
calibration_plot(data, obs = "x", pred_1 = "y")
See vignettes for more advanced functionalities, including model-based ROC, intercept adjustment, calibration plot, and unit normal loss integral in two dimensions.
You can also access the vignettes from R:
browseVignettes("predtools")