ArticleFrontiers in psychology2021
Dynamical Properties and Conceptual Interpretation of Latent Change Score Models.
Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- A Comprehensive Examination of Sex-Differentiated Correlates of Attention-Deficit/Hyperactivity Disorder Symptoms in Late Childhood and Early Adolescence.Clinical psychological science : a journal of the Association for Psychological Science · 2026Article
- Links between hormonal and pubertal development, and adolescent females' risk for affective symptoms.Psychoneuroendocrinology · 2026Article
- A Longitudinal Study of the Bidirectional Temporal Dynamics Between Body Mass Index and Biological Aging.Journal of cachexia, sarcopenia and muscle · 2025Article
- Accommodating Continuous Time Metrics within the Discrete-time Latent Change Score Model Using Definition Variables.Structural equation modeling : a multidisciplinary journal · 2025Article
- Thalamus anatomy predicts cognitive performance and hippocampal atrophy in aging adults: a UK Biobank study.Brain communications · 2025Article
- Common Cause Versus Dynamic Mutualism: An Empirical Comparison of Two Theories of Psychopathology in Two Large Longitudinal Cohorts.Clinical psychological science : a journal of the Association for Psychological Science · 2024Article
- Imagining a better world: assessing the immediate and delayed effects of imagined contact on attitudes toward refugees in elementary school.Frontiers in psychology · 2024Article
- lcsm: An R package and tutorial on latent change score modelling.Wellcome open research · 2022Article
- The Relationship Between Negative Affect, State Mindfulness, and the Role of Personality.Mindfulness · 2022Article
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Authors and funding
4 authors.
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Abstract
Latent Change Score models (LCS) are a popular tool for the study of dynamics in longitudinal research. They represent processes in which the short-term dynamics have direct and indirect consequences on the long-term behavior of the system. However, this dual interpretation of the model parameters is usually overlooked in the literature, and researchers often find it difficult to see the connection between parameters and specific patterns of change. The goal of this paper is to provide a comprehensive examination of the meaning and interpretation of the parameters in LCS models. Importantly, we focus on their relation to the shape of the trajectories and explain how different specifications of the LCS model involve particular assumptions about the mechanisms of change. On a supplementary website, we present an interactive Shiny App that allows users to explore different sets of parameter values and examine their effects on the predicted trajectories. We also include fully explained code to estimate some of the most relevant specifications of the LCS model with the R-packages
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