Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models
Abstract
We present generalized additive latent and mixed models (GALAMMs) for analysis of clustered data with responses and latent variables depending smoothly on observed variables. A scalable maximum likelihood estimation algorithm is proposed, utilizing the Laplace approximation, sparse matrix computation, and automatic differentiation. Mixed response types, heteroscedasticity, and crossed random effects are naturally incorporated into the framework....
Paper Details
Title
Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models
Published Date
Mar 28, 2023
Journal
Volume
88
Issue
2
Pages
456 - 486
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History