Event Title
Studying Developmental Growth with Multilevel Models for Linear and Categorical Change
Date of Publication
2-3-2021
Document Type
Presentation
Abstract
Methods for longitudinal modeling help gain insight into developmental processes. However, different modeling approaches allow for unique perspectives on developmental processes. We explored the development of depression using (1) multilevel growth modeling (ML-GM) and (2) multilevel latent transition analysis (ML-LTA) which conceptualize change over time in differently. ML-GM focuses on individual trajectories while ML-LTA identifies transitions through stages of depression. We used a subset of the public-use dataset, National Longitudinal Survey Youth (’97), for didactic use. Our talk and paper will focus on describing what inferences can be drawn using these different conceptual approaches
Keywords
Developmental Growth
Persistent Identifier
http://hdl.handle.net/10950/2955
Studying Developmental Growth with Multilevel Models for Linear and Categorical Change
Methods for longitudinal modeling help gain insight into developmental processes. However, different modeling approaches allow for unique perspectives on developmental processes. We explored the development of depression using (1) multilevel growth modeling (ML-GM) and (2) multilevel latent transition analysis (ML-LTA) which conceptualize change over time in differently. ML-GM focuses on individual trajectories while ML-LTA identifies transitions through stages of depression. We used a subset of the public-use dataset, National Longitudinal Survey Youth (’97), for didactic use. Our talk and paper will focus on describing what inferences can be drawn using these different conceptual approaches