Dabest

New Features

- **Standardized Delta-delta Effect Size**: We added a new metric akin to a Hedges’ g for delta-delta effect size, which allows comparisons between delta-delta effects generated from metrics with different units.

- **New Paired Proportion Plot**: This feature builds upon the existing proportional analysis capabilities by introducing advanced aesthetics and clearer visualization of changes in proportions between different groups, inspired by the informative nature of Sankey Diagrams. It's particularly useful for studies that require detailed examination of how proportions shift in paired observations.

- **Customizable Swarm Plot**: Enhancements allow for tailored swarm plot aesthetics, notably the adjustment of swarm sides to produce asymmetric swarm plots. This customization enhances data representation, making visual distinctions more pronounced and interpretations clearer.

Enhancement

- **Miscellaneous Improvements**: This version also encompasses a broad range of miscellaneous enhancements, including bug fixes, Bootstrapping speed improvements, new templates for raising issues, and updated unit tests. These improvements are designed to streamline the user experience, increase the software's stability, and expand its versatility. By addressing user feedback and identified issues, DABEST continues to refine its functionality and reliability.

This release is a complete rebuild of dabestr.

Previous functions from v0.3.0 and before are now depreciated.

Main API
This version of dabestr features a new Main API. The following functions have been sequentially organised for their intended procedural utilisation.

* `load()`
processes and converts a tidy dataset into the dabestr format.

* `mean_diff()`, `median_diff()`, `cohens_d()`, `hedges_g()`, `cliffs_delta()`, `cohens_h()`
Computes the effect size for each control-test group pairing in `idx`.

* `dabest_plot()` produces a Gardner-Altman estimation plot or a Cumming estimation plot depending on whether float_contrast is TRUE.

New features
* Plotting of shared control and repeated measures
* Proportion plots (unpaired and paired)
* Mini-Meta Delta plots
* Delta-Delta plots

New Features
- **Repeated measures**: Augments the prior function for plotting (independent) multiple test groups versus a shared control; it can now do the same for repeated-measures experimental designs. Thus, together, these two methods can be used to replace both flavors of the 1-way ANOVA with an estimation analysis.

- **Proportional data**: Generates proportional bar plots, proportional differences, and calculates Cohen’s h. Also enables plotting Sankey diagrams for paired binary data. This is the estimation equivalent to a bar chart with Fischer’s exact test.

- **The ∆∆ plot**: Calculates the delta-delta (∆∆) for 2 × 2 experimental designs and plots the four groups with their relevant effect sizes. This design can be used as a replacement for the 2 × 2 ANOVA.

- **Mini-meta**: Calculates and plots a weighted delta (∆) for meta-analysis of experimental replicates. Useful for summarizing data from multiple replicated experiments, for example by different scientists in the same lab, or the same scientist at different times. When the observed values are known (and share a common metric), this makes meta-analysis available as a routinely accessible tool.

* This is a breaking release that includes standardised effect sizes, and a bunch of bugfixes.

* This release implements the ability to supply a custom vector of colors to `palette` during plotting. There is also a bugfix that misreported the Ns for the test and control group.

* This version represents a resbumission, in response to an automated CRAN check for flavor r-patched-solaris-x86. See https://cran.r-project.org/web/checks/check_results_dabestr.html