Latent Growth Curves within Developmental Structural Equation Models

McArdle, John J.; Epstein, David

doi:10.2307/1130295

Cited by 823 publications

(548 citation statements)

References 54 publications

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“…First, the aetiological factors underlying the systematic stability (i.e., intercept) and change (i.e., slope) in CU traits throughout childhood were estimated through a biometric latent growth curve model. This highly flexible approach focuses on between-person differences in within-person change, and derives latent estimates based on all the longitudinal data available (McArdle & Epstein, 1987). In latent growth curve modelling, a heritable component to the intercept implies genetic contributions to thein systematic stability of CU traits.…”

Section: Longitudinal Twin Callous-unemotionalmentioning

confidence: 99%

A longitudinal twin study of callous-unemotional traits during childhood.

Henry

Dionne

Viding

et al. 2018

Journal of Abnormal Psychology

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Previous research indicates that genetic factors largely account for the stability of callous-unemotional (CU) traits in adolescence. However, the genetic-environmental etiology of the development of CU traits has not been extensively investigated in childhood, despite work showing the reliable measurement and stability of CU traits from a young age. The aim of this study was to investigate the temporal pattern of genetic and environmental etiology of CU traits across primary school, from school entry (7 years) to middle (9 and 10 years) and late childhood (12 years). Data were collected in a population sample of twins composed of 662 twin pairs (Quebec Newborn Twin Study). CU traits were reported by teachers and analyzed using a biometric latent growth curve model and a Cholesky decomposition model. Latent growth curve analyses revealed that genetic factors explain most of the variance in the intercept of CU traits. Individual differences in change over time were not significant. The Cholesky model revealed that genetic factors at 7 years had enduring contributions to CU traits at 9, 10, and 12 years. New, modest genetic contributions appeared at 9 and 10 years. Nonshared environmental contributions were generally age-specific. No shared environmental contributions were detected. In sum, both modeling approaches

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Section: Longitudinal Twin Callous-unemotionalmentioning

confidence: 99%

A longitudinal twin study of callous-unemotional traits during childhood.

Henry

Dionne

Viding

et al. 2018

Journal of Abnormal Psychology

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show abstract

“…Here, longitudinal methods can map unique developmental pathways, and statistical techniques such as latent-class growth curve modeling (McArdle & Epstein, 1987) or latent profile analysis (Cohan et al, 2008) can detect meaningful subgroups. For example, children with language delays can either catch up with their peers or continue to struggle; and these two groups follow different developmental pathways (Rice, 2004).…”

Section: Individual Differences Are Important (Mean Trajectories Tellmentioning

confidence: 99%

Considering Development in Developmental Disorders

Paterson

Parish‐Morris

Hirsh‐Pasek

et al. 2016

Journal of Cognition and Development

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“…LGMs are structural equation models that evaluate change over time for one or more variables at both group and individual levels (McArdle 1986;McArdle and Epstein 1987;Muthen 1989Muthen , 1991.…”

Section: Growth Curve For Outcome Domain and Total Intervention Effectsmentioning

confidence: 99%

Evaluating Mediation in Longitudinal Multivariate Data: Mediation Effects for the Aban Aya Youth Project Drug Prevention Program

Liu

Flay

2009

Prev Sci

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This study illustrates a method to evaluate mediational mechanisms in a longitudinal prevention trial, the Aban Aya Youth Project (AAYP). In previous studies, interventions of AAYP were found to be effective in reducing the growth of violence, substance use and unsafe sex among African American adolescents. In this article, we hypothesized that the effects of the interventions in reducing the growth of substance use behavior were achieved through their effects in changing intermediate processes such as behavioral intentions, attitudes toward the behavior, estimates of peers' behaviors, best friends' behaviors, and peer group pressure. In evaluating these mediational mechanisms, difficulties arise because the growth trajectories of the substance use outcome variable and some of the mediating variables were curvilinear. In addition, all of the multivariate mediational measures had planned missing data so that a score from the multiple items for a mediator could not be formed easily. In this article, we introduce a latent growth modeling (LGM) approach; namely, a two-domain LGM mediation model, in which the growth curves of the outcome and the mediator are simultaneously modeled and the mediation effects are evaluated. Results showed that the AAYP intervention effects on adolescent drug use were mediated by normative beliefs of prevalence estimates, friends' drug use behavior, perceived friends' encouragement to use, and attitudes toward the behavior.

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Latent Growth Curves within Developmental Structural Equation Models

Cited by 823 publications

References 54 publications

A longitudinal twin study of callous-unemotional traits during childhood.

A longitudinal twin study of callous-unemotional traits during childhood.

Considering Development in Developmental Disorders

Evaluating Mediation in Longitudinal Multivariate Data: Mediation Effects for the Aban Aya Youth Project Drug Prevention Program

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