# Changes in BCEA

**R on Gianluca Baio**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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I’ve just updated the GitHub’s version of `BCEA`. Andrea has done, as usual, some very nice work – this time he’s mainly focussed on the graphical engine underlying the graphs produced by `BCEA` to post-process the outcome of the economic model.

The main changes are the following:

- Added plot rendering via
`plotly`(using the command`graph=“plotly”`) to each of the functions: `ceplane.plot``eib.plot``ceac.plot``evi.plot``info.rank`- Included additional graphical output options to these functions, e.g. point_colors to
`ceplane.plot`. These are fully documented in the function help pages. - The running version has been updated to 2.3-00
- Added
`rlang`,`dplyr`to “Imports”, to solve the “*no visible binding*” note and for data manipulation functions in`info.rank`, respectively - Added
`plotly`to “Suggests” - Aligned
`info.rank`documentation to`roxygen` - Updated documentation of modified functions

In addition the objects `col` and `ICER.col` are now softly deprecated in `ceplane.plot` (where `point_colors` and `ICER_colors` are preferred).

Assuming you’ve updated `BCEA` (using for example `devtools::update_github(“giabaio/BCEA”)`) and that you have installed `plotly`, then you can test the new graphical engine using code such as the below

# Load BCEA library(BCEA) # Load the Vaccine example dataset (built-in) data(Vaccine) # Runs bcea m=bcea(e,c,ref=2,interventions=c("Status quo","Vaccine")) # And plots the results ceplane.plot(m,graph="plotly") ceac.plot(m,graph="plotly")

which produces the following graphs.

`plotly` is of course super cool in that it lets you explore elements of the graph — for example, you can hover over the points in the Cost-Effectiveness plane (the left hand side graph) and you can actually visualise the points coordinates. Similarly, when you move the cursor across the CEAC (the curve on the right hand side), `plotly` will show the actual value of the probability of cost-effectiveness.

This is actually quite exciting (as I’m playing with it right now, seems like you can do all sorts of cool things, including automatic zooming in a graph etc.).

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