API changes:

`BootGlmm`

is now`bootstrap_model`

as the primary exported function`BootCI`

is now`bootstrap_ci`

- Both of these functions should now work smoothly if your model returns a list of matrix coefficients; it will perform the bootstrap sampling on all of them
- You basically have to supply
`base_data`

to`bootstrap_model`

; to reflect this, it’s now the second argument, prior to`resamples`

- parallel functionality is improve, now supporting the
`future.apply::future_lapply`

backend (and some slightly more robust versions of e.g.`parallel::mclapply`

if desired) - Added code coverage

- For general narrowness bias, now resampling k-1 levels of random effects / n-1 rows of regular data (depending on existence of random effects). This can be turned off with narrowness_avoid = FALSE in BootGlmm.

- Added a warning if data not supplied explicitly
- Changed two-sided p-value calculation to more tightly respect the fact that the bootstrap t-values intentionally are not forced to be symmetric.

- Added a
`NEWS.md`

file to track changes to the package. - Initial release of glmmboot