Very cool! Looking forward to checking this out.

Thanks, Katie!

Reposting for the morning crowd. Check out our new preprint if you’re interested in methods for modeling ILD 👇

Many thanks to my wonderful coauthors: @jonathanpark.bsky.social, Sy-Miin Chow, Anja Ernst, Vladas Pipiras, and @fishingwithzack.bsky.social.

We conducted a simulation study to evaluate the performance of subgrouping multi-VAR across a range of factors and found that it performs well with respect to model/subgroup recovery and quality of estimates. Performance was also assessed in the context of an empirical example.

What's nice about this?

The competing penalty terms govern both the sparsity and heterogeneity of the solution. This allows for the flexible approximation of commonly encountered scenarios (e.g., minimal heterogeneity, subgroup-specific heterogeneity, etc.).

Subgrouping multi-VAR accommodates both quantitative and qualitative heterogeneity in the estimation of group-, subgroup-, and individual-level effects.

Notably, these dynamics are estimated simultaneously using a structured regularization approach.

We have a new preprint!

I'm excited to share recent work related to modeling multiple-subject, multivariate time series.

We extend the multi-VAR framework to allow for data-driven identification and penalized estimation of subgroup-specific dynamics.

arxiv.org/abs/2409.03085

My lab is recruiting graduate students for Fall 2024. If you're interested in doing research at the intersection of modeling time-dependent systems, statistical programming, and developmental science come work with me and the amazing scientists at Penn State! quantdev.ssri.psu.edu