Psychometrika, 87(2)


Special Issue on Forecasting with Intensive Longitudinal Data

Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data
Zachary F. Fisher, Younghoon Kim, Barbara L. Fredrickson, Vladas Pipiras [Google Scholar]

Guest Editors’ Introduction to the Special Issue on Forecasting with Intensive Longitudinal Data
Peter F. Halpin, Kathleen Gates, Siwei Liu [Google Scholar]

Bayesian Forecasting with a Regime-Switching Zero-Inflated Multilevel Poisson Regression Model: An Application to Adolescent Alcohol Use with Spatial Covariates
Yanling Li, Zita Oravecz, Shuai Zhou, Yosef Bodovski, Ian J. Barnett, Guangqing Chi, Yuan Zhou, Naomi P. Friedman, Scott I. Vrieze, Sy-Miin Chow [Google Scholar]

A Systematic Study into the Factors that Affect the Predictive Accuracy of Multilevel VAR(1) Models
Ginette Lafit, Kristof Meers, Eva Ceulemans [Google Scholar]

Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data
Michael D. Hunter, Haya Fatimah, Marina A. Bornovalova [Google Scholar]

A Lasso and a Regression Tree Mixed-Effect Model with Random Effects for the Level, the Residual Variance, and the Autocorrelation
Steffen Nestler, Sarah Humberg [Google Scholar]

Forecasting Intra-individual Changes of Affective States Taking into Account Inter-individual Differences Using Intensive Longitudinal Data from a University Student Dropout Study in Math
Augustin Kelava, Pascal Kilian, Judith Glaesser, Samuel Merk, Holger Brandt [Google Scholar]

Control Theory Forecasts of Optimal Training Dosage to Facilitate Children’s Arithmetic Learning in a Digital Educational Application
Sy-Miin Chow, Jungmin Lee, Abe D. Hofman, Han L. J. Maas, Dennis K. Pearl, Peter C. M. Molenaar [Google Scholar]

A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data
Esther Ulitzsch, Steffi Pohl, Lale Khorramdel, Ulf Kroehne, Matthias Davier [Google Scholar]

Better Information From Survey Data: Filtering Out State Dependence Using Eye-Tracking Data
Joachim Büschken, Ulf Böckenholt, Thomas Otter, Daniel Stengel [Google Scholar]

Semiparametric Factor Analysis for Item-Level Response Time Data
Yang Liu, Weimeng Wang [Google Scholar]

An Empirical Q-Matrix Validation Method for the Polytomous G-DINA Model
Jimmy de la Torre, Xue-Lan Qiu, Kevin Carl Santos [Google Scholar]

Modeling Conditional Dependence of Response Accuracy and Response Time with the Diffusion Item Response Theory Model
Inhan Kang, Paul Boeck, Roger Ratcliff [Google Scholar]

Transformer-Based Deep Neural Language Modeling for Construct-Specific Automatic Item Generation
Björn E. Hommel, Franz-Josef M. Wollang, Veronika Kotova, Hannes Zacher, Stefan C. Schmukle [Google Scholar]

Modeling Faking in the Multidimensional Forced-Choice Format: The Faking Mixture Model
Susanne Frick [Google Scholar]