Package index • gtstats

Teaching datasets

Built-in, labelled datasets for reproducible learning and examples.

birthwt: Low birth weight data
trial_data: Three-arm clinical trial teaching data
paired_data: Paired follow-up teaching data
outbreak_data: Oswego foodborne-outbreak line list
surveillance_data: Archived weekly US hospital-admission surveillance data

Guided interface

A point-and-click companion that generates reproducible gtstats code.

gtstats_app(): Launch the gtstats graphical interface

Understand the data

Understand variable types, missing data, and distributions before analysis.

describe_data(): Understand a dataset before analysis
assess_distribution(): Assess the empirical distribution of continuous variables
assess_variance(): Assess variation of continuous variables across groups

Describe and compare

Test whether groups differ and quantify associations.

compare_groups(): Compare groups using common inferential tests
effect_size(): Estimate an effect size
correlation(): Correlation analysis for one pair or several continuous variables

Inspect decisions

Inspect assumptions, diagnostic checks, and every analysis denominator.

assumptions_stats(): Inspect statistical assumptions
diagnostics_stats(): Inspect statistical diagnostics
denominators_stats(): Inspect statistical denominators

Plots

Visualise group comparisons and statistical outputs.

plot_compare(): Plot a group comparison
plot_correlation(): Plot the relationship between two continuous variables

Epidemiology

Proportions with Wilson score confidence intervals by default (exact binomial optional), event rates with exact Poisson confidence intervals, and 2x2 tables with RR, OR, and RD.

epi_table(): Outbreak and surveillance summary table
proportion_stats(): Proportion statistics
rate_stats(): Incidence rate with exact Poisson confidence interval
crosstabs(): Cross-tabulations with optional 2x2 epidemiological measures

Build a descriptive table

Build the descriptive foundation, then add confidence intervals, comparisons, or specialist rows only when required.

summary_table(): Create a summary table builder
add_ci(): Add confidence intervals to a summary table
add_p(): Add p-values to a descriptive table
add_proportion(): Add a proportion row to a descriptive table
add_rate(): Add an event-rate row
add_total(): Add total counts to a descriptive table
add_row(): Add a custom row to a descriptive table
add_summary(): Add summary rows to a descriptive table

Render, style, and export

Preserve already calculated tables, render as flextable by default, apply publication styling, export to Office, or opt into gt for HTML.

as_stats_table(): Convert an already summarised data frame into a publication table
customise_table(): Customize a gtstats table
to_flextable(): Convert a gtstats object to flextable
to_gt(): Convert a gtstats result to a gt table
save_output(): Save a gtstats table or plot

Print methods

S3 print methods called automatically when printing gtstats objects to the console.

print(<gt_compare>): Print a gtstats compare object
print(<gt_correlation>): Print a gtstats correlation object
print(<gt_data_table>): Print an already summarised gtstats table
print(<gt_describe>): Print a gtstats describe object
print(<gt_distribution>): Print a gtstats distribution object
print(<gt_effect>): Print a gtstats effect-size object
print(<gt_epi_table>): Print an outbreak and surveillance table
print(<gt_prop>): Print a gtstats proportion object
print(<gt_rate>): Print a gtstats rate object
print(<gt_twobytwo>): Print a gtstats 2x2 table object
print(<gt_variance>): Print a gtstats variance object
print(<gtstats_summary>): Print a descriptive table