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Reposted by Kaidi Kang

Wake Forest Statistical Sciences @wakeforeststats.bsky.social · 16/06/2025

👏 Huge congratulations to Assistant Prof @sarahlotspeich.bsky.social Lotspeich for her Societal Impact Award from the @cwstat.bsky.social! Dr. Lotspeich is being recognized for her outstanding efforts and impact on social justice through your collaboration, leadership, and partnerships.

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Kaidi Kang @kaidikang.bsky.social · 01/04/2025

Really excited to see this paper is finally out! 👇👇👇

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Kaidi Kang @kaidikang.bsky.social · 25/02/2025

Excited to reach this milestone!!

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Reposted by Kaidi Kang

Simon Vandekar @vandyatvandy.bsky.social · 22/01/2025

Don't throw out your data though! If you model separate between- and within-subject effects, you'd see that they're different! Brain-behavior associations across individuals are different than changes within individuals. You can model those separately in your own data without any fancy stats!

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Reposted by Kaidi Kang

Simon Vandekar @vandyatvandy.bsky.social · 22/01/2025

Tidbit that you can implement in your own analyses: If you collect longitudinal data you improve efficiency by throwing out half your data! WTF?! If you use baseline ("1st") versus a common longitudinal analysis ("All") effect size decreases! Read on! @kaidikang.bsky.social @meharpist.bsky.social

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Kaidi Kang @kaidikang.bsky.social · 10/12/2024

If they are accurate measurements (i.e., the participant has extreme cognitive ability on that task), then I would not consider them outliers, even if their values are extreme. (#2)

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Kaidi Kang @kaidikang.bsky.social · 10/12/2024

Thanks for the good question. If the outlier is caused by technical measurement error (i.e., the measure is not capturing what it is intended to; e.g., the person was falling asleep during the task), they should be excluded from the analysis. (#1)

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Kaidi Kang @kaidikang.bsky.social · 10/12/2024

My greatest pleasure to have worked with the amazing editor @meharpist.bsky.social, the excellent reviewers, and the awesome editorial team at Nature on our paper!! Thrilled to share our research!

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Reposted by Kaidi Kang

Mary Elizabeth Sutherland @meharpist.bsky.social · 09/12/2024

How can we increase the replicability of brain-wide association studies in a rigorous way? A new @natureportfolio.bsky.social study by @kaidikang.bsky.social et al describes the aspects of study design that improve the replicability of BWAS studies 🧪https://www.nature.com/articles/s41586-024-08260-9

nature.com

Study design features increase replicability in brain-wide association studies - Nature

Optimizing study design is critical for increasing standardized effect sizes and replicability, and the features that increase replicability in cross-sectional and longitudinal brain-wide association ...

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Kaidi Kang @kaidikang.bsky.social · 28/11/2024

Thank you @roselynechauvin.bsky.social sky.social and @ndosenbach.bsky.social for this awesome Nature News & Views on our work!

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Reposted by Kaidi Kang

Peg Duthie @plduthie.bsky.social · 27/11/2024

Vanderbilt PhD candidate Kaidi Kang @kaidikang.bsky.social is 1st author of a new paper in Nature, with associate profs Simon Vandekar (PhD @dbei-upenn.bsky.social) & Ran Tao (PhD @uncchapelhill.bsky.social), PhD candidates Jiangmei Xiong & Megan Jones... (1/2) news.vumc.org/2024/11/27/n...

news.vumc.org

New research points way to more reliable brain studies

A new study in Nature identifies research strategies for tying brain function and structure to behavior and health.

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Kaidi Kang @kaidikang.bsky.social · 28/11/2024

Thank you, Dr. Fair! It was really a rewarding experience for me to collaborate with your team from #MIDB! @drdamienfair.bsky.social @tervoclemmensb.bsky.social @bart-larsen.bsky.social Thank you for all your efforts and expertise you put into this work; they truly made this work better!

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Kaidi Kang @kaidikang.bsky.social · 27/11/2024

Hi. Just joined bluesky 😋

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