R Graphical Manual

Browse All

Last data update: 2014.03.03

R: Plots the probability that each intervention is the most...

mce.plot

R Documentation

Plots the probability that each intervention is the most cost-effective

Description

Plots the probability that each of the n_int interventions being analysed is the most cost-effective.

Usage

mce.plot(mce,pos=c(1,0.5),graph=c("base","ggplot2"))

Arguments

`mce`	The output of the call to the function `multi.ce`.
`pos`	Parameter to set the position of the legend. Can be given in form of a string `(bottom\|top)(right\|left)` for base graphics and `bottom\|top\|left\|right` for ggplot2. It can be a two-elements vector, which specifies the relative position on the x and y axis respectively, or alternatively it can be in form of a logical variable, with `TRUE` indicating to use the first standard and `FALSE` to use the second one. Default value is `c(1,0.5)`, that is on the right inside the plot area.
`graph`	A string used to select the graphical engine to use for plotting. Should (partial-)match the two options `"base"` or `"ggplot2"`. Default value is `"base"`.

Value

mceplot

A ggplot object containing the plot. Returned only if graph="ggplot2".

Author(s)

Gianluca Baio, Andrea Berardi

References

Baio, G., Dawid, A. P. (2011). Probabilistic Sensitivity Analysis in Health Economics. Statistical Methods in Medical Research doi:10.1177/0962280211419832.

Baio G. (2012). Bayesian Methods in Health Economics. CRC/Chapman Hall, London

Examples

# See Baio G., Dawid A.P. (2011) for a detailed description of the 
# Bayesian model and economic problem
#
# Load the processed results of the MCMC simulation model
data(Vaccine)
# 
# Runs the health economic evaluation using BCEA
m <- bcea(e=e,c=c,          # defines the variables of 
                            #  effectiveness and cost
      ref=2,                # selects the 2nd row of (e,c) 
                            #  as containing the reference intervention
      interventions=treats, # defines the labels to be associated 
                            #  with each intervention
      Kmax=50000,           # maximum value possible for the willingness 
                            #  to pay threshold; implies that k is chosen 
                            #  in a grid from the interval (0,Kmax)
      plot=FALSE            # inhibits graphical output
)
#
mce <- multi.ce(m)          # uses the results of the economic analysis 
#
mce.plot(mce,               # plots the probability of being most cost-effective
      graph="base")         #  using base graphics
#
if(require(ggplot2)){
mce.plot(mce,               # the same plot
      graph="ggplot2")      #  using ggplot2 instead
}

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(BCEA)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/BCEA/mce.plot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: mce.plot
> ### Title: Plots the probability that each intervention is the most
> ###   cost-effective
> ### Aliases: mce.plot
> ### Keywords: Health economic evaluation Multiple comparison
> 
> ### ** Examples
> 
> # See Baio G., Dawid A.P. (2011) for a detailed description of the 
> # Bayesian model and economic problem
> #
> # Load the processed results of the MCMC simulation model
> data(Vaccine)
> # 
> # Runs the health economic evaluation using BCEA
> m <- bcea(e=e,c=c,          # defines the variables of 
+                             #  effectiveness and cost
+       ref=2,                # selects the 2nd row of (e,c) 
+                             #  as containing the reference intervention
+       interventions=treats, # defines the labels to be associated 
+                             #  with each intervention
+       Kmax=50000,           # maximum value possible for the willingness 
+                             #  to pay threshold; implies that k is chosen 
+                             #  in a grid from the interval (0,Kmax)
+       plot=FALSE            # inhibits graphical output
+ )
> #
> mce <- multi.ce(m)          # uses the results of the economic analysis 
> #
> mce.plot(mce,               # plots the probability of being most cost-effective
+       graph="base")         #  using base graphics
> #
> if(require(ggplot2)){
+ mce.plot(mce,               # the same plot
+       graph="ggplot2")      #  using ggplot2 instead
+ }
Loading required package: ggplot2
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>