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giabaio / BCEA

Bayesian Cost Effectiveness Analysis. Given the results of a Bayesian model (possibly based on MCMC) in the form of simulations from the posterior distributions of suitable variables of costs and clinical benefits for two or more interventions, produces a health economic evaluation. Compares one of the interventions (the "reference") to the others ("comparators"). Produces many summary and plots to analyse the results
https://gianluca.statistica.it/software/bcea/
GNU General Public License v3.0
40 stars 16 forks source link

Quick getting started guide. #9

Open seabbs opened 4 years ago

seabbs commented 4 years ago

I thought your presentation based overview was really great - it would be excellent if this was included in the README.

Lots of packages have informative READMEs and I find this really helps.

Linked to #6.

giabaio commented 4 years ago

On this one, I think that the page on my website + blog and other tools there do have lots of bits & pieces on BCEA and I think --- aside from the books --- essentially all the information is there. Not a reason not to include a link to the relevant pages. Done now, so closing the issue here, but again do shout if you see something not quite clear!

seabbs commented 4 years ago

Fair enough again.

Personally, I found navigating through the blog to be a little tricky. I have also discussed the package with several people - most of them erroneously thought that a JAGS model was required so some very simple initial details might be good.

In terms of the user experience having everything within the package would be nice for the following reasons:

  1. Users can look at examples in vignettes + the README without leaving R.
  2. Once the package is installed - the internet is not required.
  3. Bringing it all into a standardized structure makes it much easier to spot documentation gaps.
  4. Having user instructions in the readme makes it much easier to get up to speed with the package. Users can then look at your other material (and book!) as they need more detail.
  5. A quick overview in the README means that users finding the package from CRAN can very quickly understand what the package does. If this is not supplied they may pass over the package.
  6. It is typically what robust R packages do. Whilst herding is not all good having this would help signal that this is a good package.

I'm not sure what the downsides to having this in the README are but obviously, this is all up to you!

giabaio commented 4 years ago

No --- there's no downside, really. Happy to discuss if you have a draft of the README that you would like to push through!