Sacha Epskamp

@sachaepskamp.bsky.social

Associate professor at the National University of Singapore

New paper— everyone is collecting intensive longitudinal data but recent review studies report that less than half of studies consider measurement/psychometrics. The paper covers a few foundational psychometric methods for ILD and provides a shiny app to apply them link.springer.com/article/10.3...

A primer on intensive longitudinal psychometrics - Behavior Research Methods

Many intensive longitudinal studies are interested in topics that are not always amenable to direct physical measurement and instead are often theorized as latent constructs (e.g., affect, emotion, mo...

link.springer.com

Thrilled to share that our work (with Sverre Urnes Johnson and @sachaepskamp.bsky.social) on invariance partial pruning (IVPP), a novel approach to comparing networks in time-series and panel data is now online at Psychological Methods 10.1037/met0000824 (preprint link: 10.31234/osf.io/vb8dz_v2).

mlVAR #Rstats 📦 version 0.6.1 is now on CRAN! Major updates include the mlGGM function for multi-level GGM estimation on nested cross-sectional data (e.g., students nested in classrooms) and the inclusion of residuals + predicted values from the mlVAR results. cran.r-project.org/web/packages...

mlVAR: Multi-Level Vector Autoregression

Estimates the multi-level vector autoregression model on time-series data. Three network structures are obtained: temporal networks, contemporaneous networks and between-subjects networks.

cran.r-project.org