Sangyu Xu

A full display of the LEGO USS Enterprise-D (NCC-1701-D) on its stand, with the entire TNG crew lineup in front—Geordi La Forge, Worf, Guinan, Data (with Spot), Captain Picard, Commander Riker, Deanna Troi, Beverly Crusher, and Wesley Crusher—all neatly arranged beneath the saucer section.

We finished! On the way out the door this morning, the kids and I attached the last piece of our #LEGO Enterprise. Fun was had by all.

13.01.2026 14:05 — 👍 3    🔁 2    💬 0    📌 0

New release announcement for JASP 0.95.0 featuring inclusion of the ESCI module

Look what you can find in the latest version of JASP:

**esci**

That's right, all your favorite estimation-focused analyses, strong hypothesis testing, and meta-analysis are available in the esci module for JASP 0.95.

#stats #metascience
Many thanks to the good people at @jaspstats.bsky.social

29.07.2025 02:27 — 👍 6    🔁 4    💬 1    📌 0

A fan of the DABEST package but want to do some multi-group analysis? Our expanded DABEST 2.0 does just that. Rethink NHST-based dichotomy and estimate the actual effect sizes with confidence intervals! Find out more in our new preprint.

01.02.2026 03:05 — 👍 3    🔁 0    💬 0    📌 0

Loading Data – dabest Loading data and relevant groups

Thanks! And yes, dabest.load() function has an argument “resamples” for this. See API (acclab.github.io/DABEST-pytho...)

01.02.2026 03:01 — 👍 2    🔁 0    💬 0    📌 0

Getting over ANOVA: Estimation graphics for multi-group comparisons Data analysis in experimental science mainly relies on null-hypothesis significance testing, despite its well-known limitations. A powerful alternative is estimation statistics, which focuses on effect-size quantification. However, current estimation tools struggle with the complex, multi-group comparisons common in biological research. Here we introduce DABEST 2.0, an estimation framework for complex experimental designs, including shared-control, repeated-measures, two-way factorial experiments, and meta-analysis of replicates. ### Competing Interest Statement The authors have declared no competing interest.

So excited to see DaBest 2.0 is out: get bootstrapped estimation statistics for simple through complex designs, all with beautiful visualization, available in R and Python.

Check it out!

Pre-print describing new features for complex designs: www.biorxiv.org/content/10.6...

#stats

29.01.2026 15:08 — 👍 4    🔁 1    💬 2    📌 0