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R: Summary plot of the health economic analysis when the mixed...

plot.mixedAn

R Documentation

Summary plot of the health economic analysis when the mixed analysis is considered

Description

Compares the optimal scenario to the mixed case in terms of the EVPI

Usage

## S3 method for class 'mixedAn'
plot(x, y.limits = NULL, pos=c(0,1), graph=c("base","ggplot2"), ...)

Arguments

`x`	An object of class `mixedAn`, given as output of the call to the function `mixedAn`.
`y.limits`	Range of the y-axis for the graph. The default value is `NULL`, in which case the maximum range between the optimal and the mixed analysis scenarios is considered.
`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 `FALSE` indicating to use the default position and `TRUE` to place it on the bottom of the plot. Default value is `c(0,1)`, that is in the topleft corner 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"`.
`...`	Arguments to be passed to methods, such as graphical parameters (see `par`).

Value

evi

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

The function produces a graph showing the difference between the ”optimal” version of the EVPI (when only the most cost-effective intervention is included in the market) and the mixed strategy one (when more than one intervention is considered in the market).

Author(s)

Gianluca Baio, Andrea Berardi

References

Baio, G. and Russo, P. (2009).A decision-theoretic framework for the application of cost-effectiveness analysis in regulatory processes. Pharmacoeconomics 27(8), 645-655 doi:10.2165/11310250

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
)
#
ma <- mixedAn(m,        # uses the results of the mixed strategy 
                        #  analysis (a "mixedAn" object)
       mkt.shares=NULL  # the vector of market shares can be defined 
                        #  externally. If NULL, then each of the T 
                        #  interventions will have 1/T market share
)
#
# Can also plot the summary graph
plot(ma,graph="base")
#
# Or with ggplot2
if(require(ggplot2)){
plot(ma,graph="ggplot2")
}

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/plot.mixedAn.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.mixedAn
> ### Title: Summary plot of the health economic analysis when the mixed
> ###   analysis is considered
> ### Aliases: plot.mixedAn
> ### Keywords: Health economic evaluation Mixed analysis
> 
> ### ** 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
+ )
> #
> ma <- mixedAn(m,        # uses the results of the mixed strategy 
+                         #  analysis (a "mixedAn" object)
+        mkt.shares=NULL  # the vector of market shares can be defined 
+                         #  externally. If NULL, then each of the T 
+                         #  interventions will have 1/T market share
+ )
> #
> # Can also plot the summary graph
> plot(ma,graph="base")
> #
> # Or with ggplot2
> if(require(ggplot2)){
+ plot(ma,graph="ggplot2")
+ }
Loading required package: ggplot2
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>