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modelROC
View on CRAN: Click
here
Download and install modelROC package within the R console
Install from CRAN:
install.packages("modelROC")
Install from Github:
library("remotes")
install_github("cran/modelROC")
Install by package version:
library("remotes")
install_version("modelROC", "1.0")
Attach the package and use:
library("modelROC")
Maintained by
Jing Zhang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
First Published: 2021-06-25
Latest Update: 2022-12-05
Description:
The ROC curve method is one of the most important and commonly usedmethods for model accuracy assessment which is one of the most important elementsof model evaluation.The modelROC package is a model-based ROC assessment tool which directly worksfor ROC analysis of regression results for logistic regression of binary variablesincluding the glm and lrm commands and COX regression for survival analysisincluding the cph and coxph commands.The most important feature of modelROC is that both the model and the independentvariables can be analysed simultaneously and for survival analysismultiple time points and area under the curve analysis are supported.Still flexible visualisation is possible with the ggplot2 package.Reference are Kelly H. Zou 1998 doi10.1002sici1097-02581997101516193C2143aid-sim6553E3.0.co2-3 andP J Heagerty 2000 doi10.1111j.0006-341x.2000.00337.x.
How to cite:
Jing Zhang (2021). modelROC: Model Based ROC Analysis. R package version 1.0, https://cran.r-project.org/web/packages/modelROC. Accessed 19 Feb. 2025.
Previous versions and publish date:
1.0 (2021-06-25 13:20)
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