ggDCA: Calculate and Plot Decision Curve

Diagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical consequences. Decision-analytic techniques allow assessment of clinical outcomes but often require collection of additional information and may be cumbersome to apply to models that yield a continuous result. Decision curve analysis is a suitable method for evaluating alternative diagnostic and prognostic strategies that has advantages over other commonly used measures and techniques. This method was described by Andrew J. Vickers (2006) <doi:10.1177/0272989X06295361>.

Version: 1.1
Depends: R (≥ 2.10), ggplot2
Imports: do, set, rms (≥ 6.0.1), base.rms, survival (≥ 3.1-12)
Published: 2020-09-06
Author: Jing Zhang [aut, cre], Zhi Jin [aut]
Maintainer: Jing Zhang <zj391120 at 163.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: ggDCA results

Documentation:

Reference manual: ggDCA.pdf

Downloads:

Package source: ggDCA_1.1.tar.gz
Windows binaries: r-devel: ggDCA_1.1.zip, r-release: ggDCA_1.1.zip, r-oldrel: ggDCA_1.1.zip
macOS binaries: r-release (arm64): ggDCA_1.1.tgz, r-oldrel (arm64): ggDCA_1.1.tgz, r-release (x86_64): ggDCA_1.1.tgz, r-oldrel (x86_64): ggDCA_1.1.tgz
Old sources: ggDCA archive

Reverse dependencies:

Reverse suggests: modelROC

Linking:

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