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cumulcalib  

Cumulative Calibration Assessment for Prediction Models
View on CRAN: Click here


Download and install cumulcalib package within the R console
Install from CRAN:
install.packages("cumulcalib")

Install from Github:
library("remotes")
install_github("cran/cumulcalib")

Install by package version:
library("remotes")
install_version("cumulcalib", "0.0.1")



Attach the package and use:
library("cumulcalib")
Maintained by
Mohsen Sadatsafavi
[Scholar Profile | Author Map]
First Published: 2024-06-13
Latest Update: 2024-06-13
Description:
Tools for visualization of, and inference on, the calibration of prediction models on the cumulative domain. This provides a method for evaluating calibration of risk prediction models without having to group the data or use tuning parameters (e.g., loess bandwidth). This package implements the methodology described in Sadatsafavi and Patkau (2024) <doi:10.1002/sim.10138>. The core of the package is cumulcalib(), which takes in vectors of binary responses and predicted risks. The plot() and summary() methods are implemented for the results returned by cumulcalib().
How to cite:
Mohsen Sadatsafavi (2024). cumulcalib: Cumulative Calibration Assessment for Prediction Models. R package version 0.0.1, https://cran.r-project.org/web/packages/cumulcalib. Accessed 04 Mar. 2025.
Previous versions and publish date:
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Complete documentation for cumulcalib
Functions, R codes and Examples using the cumulcalib R package
Full cumulcalib package functions and examples
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