A systematic study into the factors that affect the predictive accuracy of multilevel VAR(1) models

DOI10.1007/s11336-021-09803-zzbMath1491.62170OpenAlexW3210745541MaRDI QIDQ2152398

Kristof Meers, Ginette Lafit, Eva Ceulemans

Publication date: 8 July 2022

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-021-09803-z

zbMATH Keywords

cross-validationprincipal componentsmulticollinearityintensive longitudinal datalinear mixed effect models

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to psychology (62P15)

Related Items (1)

Guest editors' introduction to the special issue on forecasting with intensive longitudinal data

Uses Software

• R
• lme4
• Julia
• CHull

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Model selection in linear mixed models
• A comparison of various methods for multivariate regression with highly collinear variables
• Selecting among multi-mode partitioning models of different complexities: a comparison of four model selection criteria
• Analysis of variance -- why it is more important than ever. (With discussions and rejoinder)
• The Harris-Kaiser independent cluster rotation as a method for rotation to simple component weights
• A rationale and test for the number of factors in factor analysis
• Four simultaneous component models for the analysis of multivariate time series from more than one subject to model intraindividual and interindividual differences
• Hierarchical classes models for three-way three-mode binary data: interrelations and model selection
• Julia: A Fresh Approach to Numerical Computing
• Person‐specific versus multilevel autoregressive models: Accuracy in parameter estimates at the population and individual levels
• Hierarchical relations between methods for simultaneous component analysis and a technique for rotation to a simple simultaneous structure
• The elements of statistical learning. Data mining, inference, and prediction

This page was built for publication: A systematic study into the factors that affect the predictive accuracy of multilevel VAR(1) models