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:
- 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.).