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 |
Reference manual: | ggDCA.pdf |
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: ggDCA_1.1.tgz, r-oldrel: ggDCA_1.1.tgz |
Old sources: | ggDCA archive |
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