Package: ggscidca 0.2.3

Qiang Liu

ggscidca: Plotting Decision Curve Analysis with Coloured Bars

Decision curve analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences, requires only the data set on which the models are tested, and can be applied to models that have either continuous or dichotomous results. The 'ggscidca' package adds coloured bars of discriminant relevance to the traditional decision curve. Improved practicality and aesthetics. This method was described by Balachandran VP (2015) <doi:10.1016/S1470-2045(14)71116-7>.

Authors:Qiang Liu [aut, cre]

ggscidca_0.2.3.tar.gz
ggscidca_0.2.3.tar.gz(r-4.5-noble)ggscidca_0.2.3.tar.gz(r-4.4-noble)
ggscidca_0.2.3.tgz(r-4.4-emscripten)ggscidca_0.2.3.tgz(r-4.3-emscripten)
ggscidca.pdf |ggscidca.html✨
ggscidca/json (API)

# Install 'ggscidca' in R:
install.packages('ggscidca', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • Breastcancer - A survival data on breast cancer.
  • LIRI - A data for random forest analysis.
  • demo - A medical examination related data.
  • df_surv - A data for competitive risk modelling.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 262 downloads 7 exports 40 dependencies

Last updated 6 months agofrom:2a0de1d0f6. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-linuxOKNov 17 2024

Exports:cmprskstdcacox.tcdcadcanewcrrscidcastdcatcdca

Dependencies:classclicmprskcolorspacee1071fansifarverggplot2gluegtableisobandkernlablabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrproxyR6randomForestRColorBrewerRcppreshape2rlangscalesstringistringrsurvivaltibbleutf8vctrsviridisLitewithr