Package: ggextreme 0.1.0

ggextreme: Bar Chart Races and Interactive Plots for Clinical Research

Presentation quality charts built on 'ggplot2' that the package itself does not provide. The bar chart race interpolates values on a uniform time grid, ranks every frame on its own values and eases bars into new positions, so a reordering field stays readable. Frames are ordinary 'ggplot2' objects laid out on a fixed pixel grid, which keeps the axis and label column from drifting between them, and are encoded to GIF or MP4. Circular images, such as the bundled country flags, can be placed at the end of each bar. Causal diagrams are drawn as directed acyclic graphs whose nodes and arrows each carry a rationale and references, shown on hover and opened with clickable links on click, through 'ggiraph'; the same diagram is also available as a static 'ggplot2' object. Network plots for network meta-analysis are drawn from arm level data, with the baseline characteristics and outcomes of every arm shown side by side on click. Forest plots for 'metafor' and 'meta' fits carry each study's record and risk of bias traffic lights, and replay a cumulative meta-analysis as an animation; funnel plots shade where each study would be significant and carry the pooled estimate without it, trim and fill and the tests for small-study effects; league tables for 'netmeta' fits show the direct and indirect evidence behind every estimate. Kaplan-Meier plots read survival and the hazard ratio at any time under the pointer, beside a risk table and proportional hazards tests, and swimmer plots give each patient a lane with their responses, progression and death. Nomograms of regression models, from linear and generalized linear models to mixed, Cox, parametric survival, ordinal and multinomial models, have a handle per predictor and compute each prediction with its confidence interval in the page. Choropleth maps of the world or of any 'sf' map step or play through the years, with several measures side by side for the same year. Causal diagrams can also show which paths between an exposure and an outcome an adjustment set leaves open, by the backdoor criterion; Kaplan-Meier plots give the restricted mean survival time up to a horizon the reader can move; league tables and network plots show where each network estimate's evidence comes from; and swimmer plots can carry a waterfall of best change and each patient's course beside the lanes. Four explorers put a threshold or an assumption in the reader's hands: the cutoff of a diagnostic test, with what it means for 1,000 people at any prevalence; the strength of unmeasured confounding, with E-values; the choices of a multiverse of analyses; and the threshold that defines a responder. Plots after CINeMA judge the confidence in each estimate of a network meta-analysis in six domains, with every judgment's reason and source, and show what lies behind them: each study's contribution, the estimates against a movable range of little difference, direct against indirect evidence, and a league table and a network marked with the judgments.

Authors:Ahmad Sofi-Mahmudi [aut, cre, cph]