Package: modelROC
Title: Model Based ROC Analysis
Version: 1.0
Authors@R: 
    c(
    person("Jing","Zhang",role = c("aut", "cre"),email = "zj391120@163.com"),
    person("Zhi", "Jin", role="aut")
    )
Description: The ROC curve method is one of the most important and commonly used 
    methods for model accuracy assessment, which is one of the most important elements 
    of model evaluation.
      The 'modelROC' package is a model-based ROC assessment tool, which directly works 
    for ROC analysis of regression results for logistic regression of binary variables, 
    including the glm() and lrm() commands, and COX regression for survival analysis, 
    including the cph() and coxph() commands.
      The most important feature of 'modelROC' is that both the model and the independent 
    variables can be analysed simultaneously, and for survival analysis 
    multiple 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) <doi:10.1002/(sici)1097-0258(19971015)16:19%3C2143::aid-sim655%3E3.0.co;2-3> and
    P J Heagerty (2000) <doi:10.1111/j.0006-341x.2000.00337.x>.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.1
Depends: ggplot2
Imports: do, tmcn, ROCit, survivalROC
Suggests: ggDCA, rms
NeedsCompilation: no
Packaged: 2021-06-24 13:29:32 UTC; asus
Author: Jing Zhang [aut, cre],
  Zhi Jin [aut]
Maintainer: Jing Zhang <zj391120@163.com>
Repository: CRAN
Date/Publication: 2021-06-25 11:20:07 UTC
