galamm

Presentation at CMStatistics 2021

Slides for my presentation at CMStatistics 2021 are available here. The talk was about generalized additive latent and mixed models, which is further described in this post.

Slides from Nordic-Baltic Biometrics Conference 2021

Slides for my presentation at the Nordic-Baltic Biometrics Conference are available here.

Longitudinal modeling of age-dependent latent traits with generalized additive latent and mixed models

We present generalized additive latent and mixed models (GALAMMs) for analysis of clustered data with latent and observed variables depending smoothly on observed variables. A profile likelihood algorithm is proposed, and we derive asymptotic standard errors of both smooth and parametric terms. The work was motivated by applications in cognitive neuroscience, and we show how GALAMMs can successfully model the complex lifespan trajectory of latent episodic memory, along with a discrepant trajectory of working memory, as well as the effect of latent socioeconomic status on hippocampal development.