ceef.plot.bcea {BCEA} | R Documentation |

The line connecting successive points on a cost-effectiveness plane which each represent the effect and cost associated with different treatment alternatives. The gradient of a line segment represents the ICER of the treatment comparison between the two alternatives represented by that segment. The cost-effectiveness frontier consists of the set of points corresponding to treatment alternatives that are considered to be cost-effective at different values of the cost-effectiveness threshold. The steeper the gradient between successive points on the frontier, the higher is the ICER between these treatment alternatives and the more expensive alternative would be considered cost-effective only when a high value of the cost-effectiveness threshold is assumed. Points not lying on the cost-effectiveness frontier represent treatment alternatives that are not considered cost-effective at any value of the cost-effectiveness threshold.

## S3 method for class 'bcea' ceef.plot( he, comparators = NULL, pos = c(1, 1), start.from.origins = TRUE, threshold = NULL, flip = FALSE, dominance = TRUE, relative = FALSE, print.summary = TRUE, graph = c("base", "ggplot2"), print.plot = TRUE, ... ) ceef.plot(he, ...)

`he` |
A |

`comparators` |
Vector specifying the comparators to be included in the
frontier analysis. It must have a length > 1. Default as |

`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 |

`start.from.origins` |
Logical. Should the frontier start from the
origins of the axes? The argument is reset to |

`threshold` |
Specifies if the efficiency should be defined based on a
willingness-to-pay threshold value. If set to |

`flip` |
Logical. Should the axes of the plane be inverted? |

`dominance` |
Logical. Should the dominance regions be included in the plot? |

`relative` |
Logical. Should the plot display the absolute measures (the
default as |

`print.summary` |
Logical. Should the efficiency frontier summary be printed along with the graph? See Details for additional information. |

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

`print.plot` |
Logical. Should the efficiency frontier be plotted? |

`...` |
If |

Back compatibility with BCEA previous versions:
The `bcea`

objects did not include the generating `e`

and `c`

matrices in BCEA versions <2.1-0. This function is not compatible with
objects created with previous versions. The matrices can be appended to
`bcea`

objects obtained using previous versions, making sure that the
class of the object remains unaltered.

The argument `print.summary`

allows for printing a brief summary of the
efficiency frontier, with default to `TRUE`

. Two tables are plotted,
one for the interventions included in the frontier and one for the dominated
interventions. The average costs and clinical benefits are included for each
intervention. The frontier table includes the slope for the increase in the
frontier and the non-frontier table displays the dominance type of each
dominated intervention. Please note that the slopes are defined as the
increment in the costs for a unit increment in the benefits even if
`flip = TRUE`

for consistency with the ICER definition. The angle of
increase is in radians and depends on the definition of the axes, i.e. on
the value given to the `flip`

argument.

If the argument `relative`

is set to `TRUE`

, the graph will not
display the absolute measures of costs and benefits. Instead the axes will
represent differential costs and benefits compared to the reference
intervention (indexed by `ref`

in the `bcea`

function).

`ceplane` |
A ggplot object containing the plot. Returned only
if |

The function produces a plot of the
cost-effectiveness efficiency frontier. The dots show the simulated values
for the intervention-specific distributions of the effectiveness and costs.
The circles indicate the average of each bivariate distribution, with the
numbers referring to each included intervention. The numbers inside the
circles are black if the intervention is included in the frontier and grey
otherwise. If the option `dominance`

is set to `TRUE`

, the
dominance regions are plotted, indicating the areas of dominance.
Interventions in the areas between the dominance region and the frontier are
in a situation of extended dominance.

Andrea Berardi, Gianluca Baio

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

IQWIG (2009). General methods for the Assessment of the Relation of Benefits to Cost, Version 1.0. IQWIG, November 2009.

## create the bcea object m for the smoking cessation example data(Smoking, package = "BCEA") m <- bcea(e, c, ref = 4, Kmax = 500, interventions = treats) ## produce plot ceef.plot(m, graph = "base") ## tweak the options ## flip axis ceef.plot(m, flip = TRUE, dominance = FALSE, start.from.origins = FALSE, print.summary = FALSE, graph = "base") ## or use ggplot2 instead if(require(ggplot2)){ ceef.plot(m, dominance = TRUE, start.from.origins = FALSE, pos = TRUE, print.summary = FALSE, graph = "ggplot2") }

[Package *BCEA* version 2.4.1 Index]