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group_styling() renamed to
add_group_styling() to follow gtsummary’s
add_*() naming conventionadd_group_colors() function provides a clean,
pipeable way to add background colors to group headers
get_group_rows() and
as_gt() callsadd_group_colors() section to
styling vignette with side-by-side manual vs. convenience pattern
comparisonclean_table() now correctly handles additional
percentage formats including 0% (0.000) and
0.00% (0.00), which were previously not being converted to
dashesapply_labels_from_dictionary() improved with clearer
implementation using traditional for-loop instead of confusing
<<- side-effect assignmentstr_detect()
with base R grepl(..., perl = TRUE), reducing package
dependency footprintpurrr::walk2() with traditional for-loop in
apply_labels_from_dictionary() for improved code clarity
and maintainabilityadd_auto_labels() now displays a clearer, more
user-friendly message when automatically finding a dictionary in the
environment: “Auto-labeling from ‘dictionary’ object in your environment
(this message will only show once per session)”. The message now only
appears once per R session to reduce cluttersumExtras-package)
with notes about dependency on gtsummary internal structures and minimum
version requirementsadd_auto_labels() documentation with
comprehensive explanation of R’s ecosystem label convention, including
integration with haven, Hmisc, and ggplot2 4.0+. New documentation
clarifies how labels work across the R ecosystem using standard
"label" attributes without special packages or formatsapply_labels_from_dictionary() explaining the
implementation approach using native R attributes and ecosystem
compatibilityextras() explaining
why Monte Carlo simulation is usedvignette("labeling") - Automatic Variable
Labeling: Detailed guide to unified labeling across gtsummary
tables and ggplot2 plots. Covers R’s label attribute system, creating
and maintaining data dictionaries, automatic label discovery with
add_auto_labels(), setting label attributes with
apply_labels_from_dictionary(), label priority control via
sumExtras.preferDictionary option, and cross-package
workflows demonstrating seamless integration between gtsummary, ggplot2,
and gtvignette("styling") - Table Styling and
Formatting: Advanced techniques for creating publication-ready
tables. Covers creating visually organized tables with group headers,
styling group headers with text formatting via
group_styling(), adding background colors for emphasis with
get_group_rows(), theme management across gtsummary and gt
with use_jama_theme() and theme_gt_compact(),
and combining techniques for professional table presentationtest-labels.R providing thorough
coverage of the labeling system:
preferDictionary = TRUE modesgrepl() instead
of stringrcreate_labels() has been deprecated and removed. Users
should migrate to add_auto_labels() instead. Migration
example: Instead of
tbl_summary(label = create_labels(data, dict)), use
tbl_summary() |> add_auto_labels(dict).use_jama_theme() function for explicit JAMA
compact theme applicationuse_jama_theme()add_auto_labels() now supports
tbl_regression and tbl_uvregression objects in
addition to tbl_summary objects, enabling automatic
variable labeling for regression tables from dictionary files
(55bc540)add_auto_labels() now automatically searches the
calling environment for a dictionary object when no
dictionary is explicitly providedadd_auto_labels() can now read label attributes
directly from data as a fallback when no dictionary is found, enabling
seamless integration with {haven}, {labelled}, and other packages that
set label attributesadd_auto_labels() implements a smart label priority
hierarchy: Manual labels (set via label = list() in
tbl_summary()) always take precedence, followed by
dictionary/attribute labels (based on
sumExtras.preferDictionary option), then default variable
namesapply_labels_from_dictionary() function to set
label attributes on data from a dictionary, enabling cross-package
workflows with ggplot2 4.0+ automatic axis labeling, gt, and other
label-aware packagesoptions(sumExtras.preferDictionary) to control
label priority when both dictionary and attribute labels are available.
Default is FALSE (attributes preferred over
dictionary)group_styling() gains an indent_labels
parameter (default 0L) to control indentation of variable
labels under group headers. Set to 4L to preserve
gtsummary’s default group indentation behaviorextras() gains a last parameter to control
Overall column position (default FALSE aligns with
gtsummary::add_overall() behavior)extras() gains a .args parameter to accept
a list of arguments, allowing programmatic control of pval,
overall, and last parametersadd_auto_labels() now gracefully handles missing
dictionaries by falling back to label attributes instead of erroring,
improving robustness in workflows where dictionary availability
variesgtsummary::all_tests() in
extras() functionclean_table() to avoid false
positives (e.g., matching "..." or " ")extras() now warns when add_overall() or
add_p() fail instead of silently continuingmodify_indent() column parameter in
group_styling() - column name now properly quoted as
“label” to ensure correct indentation when rendering vignettes in
pkgdownextras() to warn when called with unsupported
table types (tbl_regression, tbl_strata, non-stratified tables) instead
of silently skipping featuresclean_table() handling of tbl_strata
objects by detecting when var_type column is missingadd_auto_labels() to avoid double iteration
when extracting variable names and labelsuse_jama_theme() usage in Quick
Startuse_jama_theme() to function reference listextras() function for streamlined gtsummary table
stylingclean_table() for standardized missing value
displayadd_auto_labels() and
create_labels() for automatic variable labelingtheme_gt_compact() for JAMA-style gt table
themesgroup_styling() for enhanced group header
formattingThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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