A Dynamic approach to control for cohort differences in maturation speed using accelerated longitudinal designs

Accelerated longitudinal designs (ALD) allow studying developmental processes usually spanning multiple years in a much shorter time framework by including participants from different age cohorts, which are assumed to share the same population parameters. However, different cohorts may have been exp...

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Detalles Bibliográficos
Autores: Cáncer, Pablo F., Estrada Alonso, Eduardo, Ferrer, Emilio
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/712413
Acceso en línea:http://hdl.handle.net/10486/712413
https://dx.doi.org/10.1080/10705511.2022.2163647
Access Level:acceso abierto
Palabra clave:accelerated longitudinal designs
cohort differences
continuous time models
latent change score models
speed of maturation
state space models
Psicología
Descripción
Sumario:Accelerated longitudinal designs (ALD) allow studying developmental processes usually spanning multiple years in a much shorter time framework by including participants from different age cohorts, which are assumed to share the same population parameters. However, different cohorts may have been exposed to dissimilar contextual factors, resulting in different developmental trajectories. If such differences are not accounted for, the generating process will not be adequately characterized. In this paper, we propose a continuous-time latent change score model as an approach to capture cohort differences affecting the speed of maturation of psychological processes in ALDs. This approach fills an important gap in the literature because, until now, no method existed for this goal. Using a Monte-Carlo simulation study, we show that the proposed model detects cohort differences adequately, regardless of their size in the population. Our proposed model can help developmental researchers control for cohort effects in the context of ALDs