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"), ...)bcea object containing the results of the Bayesian modelling and the economic evaluation. The list needs to include the e and c matrices used to generate the object; see Details.NULL includes all the available comparators.(bottom|top)(right|left) for base graphics and bottom, top, left or right for ggplot2. It can be a two-elements FALSE if the average effectiveness and/or costs of at least one comparator are negative.NULL (the default), no conditions are included on the slope increase. If a positive value is passed as argument, to be efficient an interveFALSE) or the differential outcomes versus the reference comparator?"base" or "ggplot2". Default value is "base".graph="ggplot2" and a named theme object is supplied, it will be added to the ggplot object. Ignored if graph="base". Setting the argument include.ICER to TRUE will print the ICERs in the summary tablgraph="ggplot2".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.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="" 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).
2.1-0.>IQWIG (2009). General methods for the Assessment of the Relation of Benefits to Cost, Version 1.0. IQWIG, November 2009.
bcea### create the bcea object m for the smoking cessation example
data(Smoking)
m <- bcea(e,c,ref=4,Kmax=500,interventions=treats)
### produce the plot
ceef.plot(m,graph="base")
### tweak the options
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")
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