Package: ggpower 0.1.2

Yaoxiang Li

ggpower: Publication-Ready Power Analysis and Visualization

Provides statistical power analysis and sample size calculations for t-tests, ANOVA, regression, chi-square, proportion, correlation, nonparametric, biomarker, and clinical trial designs. Includes a scriptable API via power_compute(), publication-ready 'ggplot2' visualizations, and an optional 'Shiny' application.

Authors:Yaoxiang Li [aut, cre]

ggpower_0.1.2.tar.gz
ggpower_0.1.2.tar.gz(r-4.7-any)ggpower_0.1.2.tar.gz(r-4.6-any)
ggpower_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ggpower/json (API)

# Install 'ggpower' in R:
install.packages('ggpower', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yaoxiangli/ggpower/issues

Pkgdown/docs site:https://yaoxiangli.github.io

On CRAN:

Conda:

4.56 score 72 scripts 26 exports 55 dependencies

Last updated from:4777d3fdd9. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK150
source / vignettesOK229
linux-release-x86_64OK153
wasm-releaseOK138

Exports:effect_size_deffect_size_feffect_size_f2effect_size_f2_increaseeffect_size_heffect_size_qeffect_size_weta2_from_fformat_result_htmlggpower_calculatorggpower_resultggpower_t_one_sampleggpower_testsggpower_ttestodds_ratio_from_probsplot_distributionplot_power_curvepower_computepower_t_one_samplepower_t_pairedpower_t_two_sampler2_from_f2run_appsave_distribution_plotsave_power_plottheme_ggpower

Dependencies:askpassattemptbase64encbs4Dashbslibcachemclicodetoolscommonmarkconfigcpp11curldigestfarverfastmapfontawesomefreshfsggplot2gluegolemgtablehtmltoolshttpuvhttrisobandjquerylibjsonlitelabelinglaterlifecyclemagrittrmemoisemimeopensslotelpromisesR6rappdirsRColorBrewerRcpprlangrstudioapiS7sassscalesshinysourcetoolssysvctrsviridisLitewaiterwithrxtableyaml

Analysis Modes
A priori — sample size | Post hoc — achieved power | Criterion — alpha | Sensitivity — effect size | Compromise — alpha and beta ratio | Effect size conversions | Calculator | Related
Rendered fromanalysis-modes.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Biomarker Endpoints
Differential expression | ROC and AUC | Diagnostic accuracy | Survival (log-rank) | Cox prognostic models | Multiplicity and FDR | Related
Rendered frombiomarker-endpoints.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Choosing a Power Analysis
Example: Planning a One-Sample Mean Test | Choosing tests | Sidebar modules | Related
Rendered fromchoosing-a-power-analysis.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Clinical Trials
Phase III superiority | Non-inferiority | Equivalence (TOST) | Simon two-stage (Phase II) | Cluster RCT | Survival endpoints | Binary and count endpoints | Related
Rendered fromclinical-trials.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Getting Started with the GUI
In plain English | Sidebar modules | Launch the app | Typical workflow | Worked example (script) | Related analyses
Rendered fromgetting-started-gui.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Reference Validation
Example 1: One-sample t, a priori | Example 2: Multiple regression omnibus, post hoc | Example 3: ANOVA special, post hoc | Example 4: Two-sample t, unequal n, post hoc | Recommended tolerances | Related
Rendered fromreference-validation.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Scenario Guide
Implemented scenarios (48 tests) | Power Workspace (30 tests) | Biomarker Discovery (7 tests) | Clinical Trials (11 tests) | Decision table | Not yet implemented | Related
Rendered fromscenario-guide.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Support Matrix
Coverage table | Counts by module | Mode restrictions | Vignette index | Related analyses
Rendered fromsupport-matrix.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

t Tests
One sample | Two independent means | Matched pairs | Point-biserial correlation | Linear regression slope | Two-group slope difference | Generic t (direct NCP) | Related
Rendered fromt-tests.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Workspace Test Families
ANOVA and regression | Exact and proportion tests | Correlation and z tests | Logistic and Poisson regression | Nonparametric tests | Related
Rendered fromworkspace-test-families.Rmdusingknitr::rmarkdown

Last update: 2026-07-10
Started: 2026-07-10

Readme and manuals

Help Manual

Help pageTopics
Effect-size helper functionseffect_size_d effect_size_f effect_size_f2 effect_size_f2_increase effect_size_h effect_size_q effect_size_w eta2_from_f odds_ratio_from_probs r2_from_f2
Format a ggpower result as structured HTML for Shiny UIformat_result_html
Evaluate a ggpower calculator scriptggpower_calculator
Create a ggpower result objectggpower_result print.ggpower_result
Plot Power Curve for a One-Sample t-Testggpower_t_one_sample
List supported statistical power testsggpower_tests
Plot Power Curve for a Two-Sample t-Testggpower_ttest
Plot H0 and H1 distributionsplot_distribution
Plot a power curveplot_power_curve
Compute statistical power analysespower_compute
Compute Power for a One-Sample t-Testpower_t_one_sample
Compute power for a paired-samples t-testpower_t_paired
Compute Power for a Two-Sample t-Test (Equal Sample Sizes)power_t_two_sample
Run the Shiny Applicationrun_app
Save a ggpower plotsave_distribution_plot save_power_plot
Publication-ready ggpower themetheme_ggpower