Advances in Latent Variable Mixture Models

Abstract

Editors' Introduction, Gregory R. Hancock and Karen M. Samuelsen. Acknowledgments. Latent Variable Hybrids: Overview of Old and New Models, Bengt Muthen. PART I: Multilevel and Longitudinal Systems. Multilevel Mixture Models, Tihomir Asparouhov and Bengt Muthen. Longitudinal Modeling of Population Heterogeneity: Methodological Challenges to the Analysis of Empirically Derived Criminal Trajectory Profiles, Frauke Kreuter and Bengt Muthen. Examining Contingent Discrete Change Over Time with Associative Latent Transition Analysis, Brian P. Flaherty. Modeling Measurement Error in Event Occurrence for Single, Non-Recurring Events in Discrete-Time Survival Analysis, Katherine E. Masyn. PART II: Models for Assessment and Diagnosis. Evidentiary Foundations of Mixture Item Response Theory Models, Robert J. Mislevy, Roy Levy, Marc Kroopnick, and Daisy Rutstein. Examining Differential Item Functioning from a Latent Mixture Perspective, Karen M. Samuelsen. Mixture Models in a Developmental Context, Karen Draney, Mark Wilson, Judith Gluck, and Christiane Spiel. Applications of Stochastic Analyses for Collaborative Learning and Cognitive Assessment, Amy Soller and Ron Stevens. The Mixture General Diagnostic Model, Matthias von Davier. PART III: Challenges in Model Evaluation. Categories or Continua? The Correspondence Between Mixture Models and Factor Models, Eric Loken and Peter Molenaar. Applications and Extensions of the Two-Point Mixture Index of Model Fit, C. Mitchell Dayton. Identifying the Number of Classes in Growth Mixture Models, Davood Tofighi and Craig K. Enders. Choosing a Correct Factor Mixture Model: Power, Limitations, and Graphical Data Exploration, Gitta H. Lubke and Jeffrey R. Spies. About the Contributors.