Estimation Stats @EstimationStats
The official twitter account for https://t.co/Smhdl3aYG0, by the @adamcchang lab. estimationstats.com Singapore Joined April 2018-
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We hope you get a chance to use DABEST v2024.03.29 in your work. We hope to hear your feedback here and on GitHub. Refreshed documentation and tutorial can be found at acclab.github.io/DABEST-python 🧵6/6
Contributors to this update were: Zinan LU (github.com/Jacobluke-), Kah Seng LIAN (github.com/sunroofgod), A. Rosa Castillo (github.com/cyberosa). 🧵5/6
Today we are excited to launch DABEST Version 2 aka “Ondeh” , which adds entirely new statistical graphics for paired proportions, standardized delta-delta effect size, and gives new options for dot swarms. 🧵1/6
② Users may add a baseline error curve to shared control contrast plots, displayed below the control group. This is the distribution of the bootstrapped mean differences from comparing the control against itself and is a measure of inherent variability within the control group.
We have also added several features not yet present in the Python version of the package: ① As you may have noticed from the images in the thread below, we have adopted asymmetrical swarmplots, thereby better showing the distribution underlying the raw data.
Exciting news for dabestr users! We are releasing dabestr version “Lapis” (v2023.9.12), which adds estimation graphics for four new data types: repeated measures, 2 × 2 designs, proportions, and easy meta-analyses. 🧵
Updated documentation for the R package can be found at: acclab.github.io/dabestr/
Contributors to this update were: Kah Seng LIAN (github.com/sunroofgod), Zhuoyu WANG (@LucasZhuoyu, github.com/Lucas1213WZY), and Jun Yang LIAO (github.com/junyangliao)
Exciting news for dabestr users! We are releasing dabestr version “Lapis” (v2023.9.12), which adds estimation graphics for four new data types: repeated measures, 2 × 2 designs, proportions, and easy meta-analyses. 🧵
How do dabestr users prefer to get future releases? (2/2) #rstats #DataScience
📢To our R users: We will soon release a new version of dabestr (acclab.github.io/dabestr/) with brand new goodies such as repeated measures, proportion plot, mini-meta and delta-delta. #rstats #datascience We want to know how you prefer to get the package (poll in next tweet): 1/2
(Apologies for redoing this tweet thread, our previous images were showing up as sensitive content. This has now been fixed.)
An early testimonial for v2023.02.14: x.com/MathuruLab/sta…
@EstimationStats @SangyuXu @jacuzzijo @_Jacobluke @ZhangRou99 @myish_irl @adamcchang A very useful update @SangyuXu, @adamcchang and everyone else involved. We are already using it! 👍🏾
Today we are excited to launch DABEST’s first major update. The Python library now offers four new functions: repeated measures, the ∆∆ plot (‘delta-delta’), proportional plot, and mini-meta plot. These expand DABEST’s capabilities to more complex experimental designs. 🧵1/13
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