Data Registration

[ddsjoberg]

What changes are proposed in this pull request?

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Reference GitHub issue associated with pull request. e.g., 'closes #'

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Pre-review Checklist (if item does not apply, mark is as complete)

• All GitHub Action workflows pass with a ✅
• PR branch has pulled the most recent updates from master branch: usethis::pr_merge_main()
• If a bug was fixed, a unit test was added.
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Reviewer Checklist (if item does not apply, mark is as complete)

• If a bug was fixed, a unit test was added.
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When the branch is ready to be merged:

• Update NEWS.md with the changes from this pull request under the heading "# cards (development version)". If there is an issue associated with the pull request, reference it in parentheses at the end update (see NEWS.md for examples).
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Optional Reverse Dependency Checks:

Install checked with pak::pak("Genentech/checked") or pak::pak("checked")

# Check dev versions of `cardx`, `gtsummary`, and `tfrmt` which are in the `ddsjoberg` R Universe
Rscript -e "options(checked.check_envvars = c(NOT_CRAN = TRUE)); checked::check_rev_deps(path = '.', n = parallel::detectCores() - 2L, repos = c('https://ddsjoberg.r-universe.dev', 'https://cloud.r-project.org'))"

# Check CRAN reverse dependencies but run tests skipped on CRAN
Rscript -e "options(checked.check_envvars = c(NOT_CRAN = TRUE)); checked::check_rev_deps(path = '.', n = parallel::detectCores() - 2, repos = 'https://cloud.r-project.org')"

# Check CRAN reverse dependencies in a CRAN-like environment
Rscript -e "options(checked.check_envvars = c(NOT_CRAN = FALSE), checked.check_build_args = '--as-cran'); checked::check_rev_deps(path = '.', n = parallel::detectCores() - 2, repos = 'https://cloud.r-project.org')"

[ddsjoberg]

From a talk with @bzkrouse

1. Update the structure of the data description to be a named list of lists: list(ADSL = list(data_label = "Age > 60"), ADAE = list(data_label = "TEAE"))
2. Update/add the print method for the above object, so it's readable when printed in the data frame. This could even be something simple like <data description> and we have a helper to descirbe the input data sets.
3. Remove filter_expr argument and make the label mandatory.
4. Rename filter_label argument to data_label or maybe even just label.

@bzkrouse will address these points