flextable output as the default
table format across package table functions, while retaining
gt and tibble-style outputs where appropriate.approach = logit and
format = flextable.adjust_for support for adjusted multivariable
workflows, including downstream regression plots and combined regression
plots.uni_reg() and
multi_reg() via model_stats = TRUE, with AIC,
BIC, log-likelihood, deviance, pseudo R-squared, linear-model R-squared,
and model N stored in $model_stats.approach = "firth" /
approach = firth for Firth penalized logistic regression in
uni_reg(), multi_reg(),
stratified_uni_reg(), and
stratified_multi_reg(), with OR tables and compatibility
with regression plots and forest plot helpers.data_endometrial, a classic endometrial cancer
dataset with a separation pattern, for teaching and testing Firth
logistic regression.cox_reg() for Cox proportional hazards regression
using time, event, exposures, and
optional adjust_for, returning HR and adjusted HR
tables.surv_reg() for parametric survival regression
using time, event, exposures,
optional adjust_for, and a selectable survival
distribution, returning time-ratio tables.stratifier argument in cox_reg() and
surv_reg(), with stratum-specific N, event counts, and
formatted regression tables.km_plot() for Kaplan-Meier survival curves with
optional confidence intervals, censoring marks, log-rank p-values, and
number-at-risk tables.km_plot(), including
y-axis limits, percentage-scale display, optional grid removal, theme
selection, confidence interval styling, and title/subtitle sizing for
patchwork-style figure panels.km_risk_table() for standalone Kaplan-Meier risk
tables at requested follow-up times, with at-risk, event, and censored
counts.rmst_table() for restricted mean survival time
summaries up to a chosen follow-up time, with optional two-group RMST
difference.surv_model_compare() for comparing candidate
parametric survival distributions by AIC, BIC, log-likelihood, scale,
events, and N.plot_surv_fit() for visually comparing observed
Kaplan-Meier curves with fitted parametric survival curves.surv_predict() for model-based survival
probability predictions from fitted parametric survival regression
models.survival_summary() for Kaplan-Meier median
survival summaries with total N, events, censored counts, and
publication-style table outputs.survival_quantiles() for Kaplan-Meier survival
time quantiles, including event percentiles, corresponding survival
probabilities, and confidence intervals.survival_prob() for Kaplan-Meier survival
probabilities at fixed follow-up times, with at-risk, event, censored,
and confidence interval columns.logrank_test() for formal comparison of
Kaplan-Meier survival curves, with observed and expected events plus
formatted p-value output.check_ph() for proportional hazards screening of
Cox models using Schoenfeld residual tests, with flextable, gt, and
tibble outputs.plot_model_fit() for visual model diagnostics
from fitted lm/glm models and from models
stored in uni_reg() and multi_reg()
outputs.mediation_analysis() for regression-based
mediation analysis with formatted direct, indirect, total, and
proportion mediated tables.plot_mediation() for drawing a mediation path
diagram from mediation_analysis() outputs.data_diabetes_mediation, a health-related
diabetes teaching dataset for practicing obesity, glucose, and diabetes
mediation workflows.compare_models() for publication-ready comparison
of fitted gtregression model outputs, including AIC, BIC,
log-likelihood, likelihood ratio statistics, primary exposure estimates,
percent change, analysis-sample checks, and highlighted best-fit
summaries.save_forest() for exporting
forest_reg() outputs with reproducible sizing across
graphics devices and operating systems.labelled::var_label(), across descriptive,
regression, stratified, merged, plotted, and forest-style outputs.dissect(), select_models(),
interaction_models(), and
identify_confounder().identify_confounder() to support confounding assessment
alongside crude and adjusted model comparisons.dev/manual-tests/
for real-time testing of logistic, linear, log-binomial, robust Poisson,
Poisson, negative binomial, Cox, parametric survival, Firth, and
mediation workflows.descriptive_table(), uni_reg(),
multi_reg(), stratified_uni_reg(), and
stratified_multi_reg() documentation with clearer examples
using package datasets.merge_tables() so descriptive, crude, and
adjusted tables can be combined more reliably, including when visible
variable labels differ between input tables.modify_table() so merged tables retain clean
headers, spanners, and footnotes after relabelling.forest_df() and forest_reg()
support for descriptive summaries combined with univariable and
multivariable regression outputs.forest_df() and forest_reg()
support for stratified regression outputs, including one-object
stratified forest plots with highlighted stratum headers and preserved
row order.cox_reg() and
surv_reg() outputs work with plot_reg(),
plot_reg_combine(), forest_df(),
forest_reg(), merge_tables(),
modify_table(), and select_models().cox_reg() and surv_reg()
consistency with the rest of the package: both now support single
multivariable models, adjusted exposure workflows, interaction terms,
stratified workflows, and coherent table labels.compare_models() output so user-supplied or
object-derived model names are displayed instead of generic model
labels, and context-aware warnings distinguish same-sample comparisons
from different-sample comparisons.save_table() handling for wide Word tables by
preferring landscape orientation before reducing font size, respecting
minimum font sizes, and allowing users to turn width fitting off.save_docx(table_width = ...) available for custom document
layouts.select_models() output so formatted tables
clearly report the model selection direction used.merge_tables() flextable headers so internal
merge suffixes such as _p1, _p2, and
_p3 are not shown in rendered tables.merge_tables() row alignment when descriptive and
regression tables contain the same variables but different visible
labels.modify_table() handling of merged flextable
outputs so clean subheaders and group spanners are preserved.check_convergence() so failed multivariable model
fits return a clear non-converged table rather than failing during table
formatting.time, event, and
the current exposure rather than using a single complete-case dataset
across all exposures.survival model
functions, while negative follow-up times remain invalid.forest_df() row-order handling after joins and
merges so forest plots follow the same display order as the source
regression table.data_SynthDiabetes, a
synthetic replacement based on mlbench::SynthDiabetes2
(mlbench >= 2.1-11), and regenerated all mediation teaching fixtures
that depended on the prior dataset.plot_reg(),
plot_reg_combine()).
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.