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This vignette will demonstrate a simple cost-effectiveness analysis using BCEA using the smoking cessation data set contained in the package.

library(BCEA)
#> 
#> Attaching package: 'BCEA'
#> The following object is masked from 'package:graphics':
#> 
#>     contour

Load the data.

data(Smoking)

This study has four interventions.

treats <- c("No intervention", "Self-help", "Individual counselling", "Group counselling")

Setting the reference group (ref) to Group counselling and the maximum willingness to pay (Kmax) as 500

bcea_smoke <- bcea(eff, cost, ref = 4, interventions = treats, Kmax = 500)

We can easily create a grid of the most common plots

library(ggplot2)
#> Warning: package 'ggplot2' was built under R version 4.1.3

plot(bcea_smoke)

Individual plots can be plotting using their own functions.

ceplane.plot(bcea_smoke, comparison = 2, wtp = 250)


eib.plot(bcea_smoke)


contour(bcea_smoke)


ceac.plot(bcea_smoke)


ib.plot(bcea_smoke)
#> NB: k (wtp) is defined in the interval [0 - 500]