APS
2025 APS Annual Convention
Machine Learning Approaches for Modeling Intensive Longitudinal Data
Subject Area: Methodology
As a discipline psychology has long wrestled with the promise of big data for a precise accounting of human behavior and mental life. In this symposium we will discuss recent work to address these challenges by combining ideas from traditional dynamic modeling with techniques from machine learning and computational statistics.
Chairs & Discussants
- Zachary FisherChair
Pennsylvania State University, University Park
Presentations
- Intra- and Inter-Individual Differences in Affect Forecasting with Machine Learning MethodsSy-Miin Chow
- Multilevel Statistical Inference from Machine Learning Tools Using Surrogate Data Analysis Timothy Brick
- Fused Approaches for Multiple-Subject Time-Varying Parameter Models Zachary Fisher
