Package index • ggextreme

Building a race

Turn a panel of observations into frames, then draw or encode them.

ggrace(): Build a bar chart race
race_frame(): Draw one frame of a bar chart race
race_size(): The pixel size of a race frame
animate_race(): Render a bar chart race to a file

Appearance

Colors, theme and the images that sit on the bars.

race_palette(): Colors used by the bar chart race
theme_race(): The bare theme a race frame is drawn on
race_flags(): Bundled circular country flags
race_flag_codes(): Countries the bundled flags cover

Causal diagrams

Draw a DAG whose nodes and arrows explain themselves.

ggcausal(): Draw an interactive causal diagram

Network plots

Draw the network of a network meta-analysis from arm level data.

ggnma(): Draw an interactive network plot for a network meta-analysis

Meta-analysis

Forest plots and league tables for fitted models.

ggmeta(): Draw an interactive forest plot for a meta-analysis
animate_meta(): Animate a cumulative meta-analysis
ggfunnel(): Draw an interactive funnel plot for a meta-analysis
ggleague(): Draw an interactive league table for a network meta-analysis

Confidence in a network meta-analysis

Judge every estimate of a network meta-analysis in CINeMA’s six domains, and see what lies behind each judgment.

cinema_judge(): Judge confidence in the results of a network meta-analysis
cinema_league(): Draw a league table with a CINeMA confidence profile in every cell
cinema_contribution(): Draw where each network estimate's evidence comes from, study by study
cinema_clinical(): Draw network estimates against a range of little difference
cinema_incoherence(): Draw direct, indirect and network estimates side by side
cinema_network(): Draw a network plot with a strand for every study, colored by its judgment

Survival and trials

Kaplan-Meier plots with a linked risk table, proportional hazards tests and restricted mean survival, swimmer plots of each patient’s course with a waterfall and trajectories, and responder thresholds.

ggkm(): Draw an interactive Kaplan-Meier plot
animate_km(): Animate a Kaplan-Meier plot
ggswimmer(): Draw an interactive swimmer plot
ggresponder(): Draw an interactive responder threshold plot

Tests, bias and robustness

Explore the cutoff of a diagnostic test, the strength of unmeasured confounding and a multiverse of analyses.

ggdiagnostic(): Draw an interactive diagnostic threshold explorer
ggsensitivity(): Draw an interactive bias and tipping point explorer
ggmultiverse(): Draw an interactive multiverse of analyses

Prediction models

Nomograms of regression models, with a handle per predictor and the prediction computed in the page.

ggnomogram(): Draw an interactive nomogram for a regression model
nomogram_predict(): Predict from a nomogram

Maps

Choropleth maps that step or play through the years, with measures side by side.

ggchoropleth(): Draw an interactive choropleth map over time
animate_choropleth(): Animate a choropleth map

Using a graph

Turn any of the interactive graphs into a widget, a ggplot or a file.

graph_widget() graph_plot() graph_save() knit_print(<ggx_graph>) knit_print(<ggrace>): Use an interactive graph as a widget, a ggplot or a file

Data

clefts_qci: Quality of Care Index for orofacial clefts, 1990 to 2019
clefts_qci_world: Quality of Care Index for orofacial clefts in every country, 1990 to 2019
cleft_dag: An illustrative causal diagram for maternal smoking and orofacial clefts
psoriasis_nma: Arm level data from five trials in plaque psoriasis

Package

ggextreme ggextreme-package: ggextreme: Bar Chart Races and Interactive Plots for Clinical Research