plot.CEriskav {BCEA} | R Documentation |

## Plots EIB and EVPI for the Risk Aversion Case

### Description

Summary plot of the health economic analysis when risk aversion is included.

### Usage

```
## S3 method for class 'CEriskav'
plot(x, pos = c(0, 1), graph = c("base", "ggplot2"), ...)
```

### Arguments

`x` |
An object of the class |

`pos` |
Parameter to set the position of the legend (only relevant for
multiple interventions, ie more than 2 interventions being compared).
Can be given in form
of a string |

`graph` |
A string used to select the graphical engine to use for
plotting. Should (partial-)match the two options |

`...` |
Arguments to be passed to methods, such as graphical parameters
(see |

### Details

Plots the Expected Incremental Benefit and the Expected Value of Perfect Information when risk aversion is included in the utility function.

### Value

`list(eib` , `evi)` |
A two-elements named list of the ggplot objects
containing the requested plots. Returned only if |

The function produces two plots for the risk aversion analysis. The first
one is the EIB as a function of the discrete grid approximation of the
willingness parameter for each of the possible values of the risk aversion
parameter, `r`

. The second one is a similar plot for the EVPI.

### Author(s)

Gianluca Baio, Andrea Berardi

### References

Baio G, Dawid aP (2011).
“Probabilistic sensitivity analysis in health economics.”
*Stat. Methods Med. Res.*, 1–20.
ISSN 1477-0334, doi:10.1177/0962280211419832, https://pubmed.ncbi.nlm.nih.gov/21930515/.

Baio G (2013).
*Bayesian Methods in Health Economics*.
CRC.

### See Also

### 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=eff, c=cost, # 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
)
#
# Define the vector of values for the risk aversion parameter, r, eg:
r <- c(1e-10, 0.005, 0.020, 0.035)
#
# Run the cost-effectiveness analysis accounting for risk aversion
CEriskav(m) <- r
#
# produce the plots
plot(m)
## Alternative options, using ggplot2
plot(m, graph = "ggplot2")
```

*BCEA*version 2.4.6 Index]