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A set of simplified functions for creating funnel plots for proportion data. This package supports user defined benchmarks, confidence limits and estimation methods (i.e. exact or approximate) based on Spiegelhalter (2005) <doi:10.1002/sim.1970>. Additional routines for returning scored unit level data according to a set of specifications is also implemented for convenience. Specifically, both a categorical and a continuous score variable is returned to the sample data frame, which identifies which observations are deemed extreme or in control. Typically, such variables are useful as stratifications or covariates in further exploratory analyses. Lastly, the plotting routine returns a base funnel plot ('ggplot2'), which can also be tailored.
Version: | 0.1.0 |
Imports: | stats, ggplot2 (≥ 2.2.1) |
Suggests: | knitr, rmarkdown |
Published: | 2018-03-14 |
DOI: | 10.32614/CRAN.package.funnelR |
Author: | Matthew Kumar |
Maintainer: | Matthew Kumar <mattkumar at gmail.com> |
License: | GPL-3 |
URL: | https://matt-kumar.shinyapps.io/funnel/ |
NeedsCompilation: | no |
CRAN checks: | funnelR results |
Reference manual: | funnelR.pdf |
Vignettes: |
Introduction |
Package source: | funnelR_0.1.0.tar.gz |
Windows binaries: | r-devel: funnelR_0.1.0.zip, r-release: funnelR_0.1.0.zip, r-oldrel: funnelR_0.1.0.zip |
macOS binaries: | r-release (arm64): funnelR_0.1.0.tgz, r-oldrel (arm64): funnelR_0.1.0.tgz, r-release (x86_64): funnelR_0.1.0.tgz, r-oldrel (x86_64): funnelR_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
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