Modeling Behavior as Dynamic Sequential States: Introduction to the Special Issue. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Flaherty, Brian P.; Scheier, Lawrence M.
• Other Names: Scheier Lawrence M. guest-editor.; Flaherty Brian P. guest-editor.
• Is Part Of: Evaluation & the health professions. Volume 44:Issue 1(2021)
• Page Start: 3
• Page End: 8
• Publication Date: 2021-03
• Subjects: dynamic sequential states -- latent transition analysis -- developmental studies -- modeling change states -- latent class analysis; Medical care -- Evaluation -- Periodicals; Medicine -- Ability testing -- Periodicals; 362.105
• DOI: 10.1177/0163278720985917
• Languages: English
• ISSNs: 0163-2787

Abstract

This special issue of Evaluation and The Health Professions focuses on applications and extensions of latent transition analysis (LTA), a longitudinal parameterization of the latent class (LC) model. LTA is a model of discrete or qualitative change over time among potentially complex states (e.g., patterns of recent drug use or abuse experiences), commonly referred to as latent classes, latent profiles, or latent statuses. Frequently, researchers will distinguish the term "classes" for cross-sectional studies and with LTA use "statuses" to indicate the concept of "dynamic change" with individuals shifting in their response patterns and associated statuses over time. It goes without saying that LTA models are underutilized, although quite flexible. This special issue showcases articles that apply LTA and extend the capabilities of this approach to modeling discrete change in new ways.