Interaction Effects in Latent Growth Models: Evaluation of Alternative Estimation Approaches

Background. Higher education has been posited to protect against cognitive decline, either because the rate of decline is slower in the more highly educated or the start of decline is delayed. Latent growth models provide improved methodology to examine this issue.Methods. The sample consisted of 887 participants aged 70–93 years in 1991 and followed up in 1994 and 1998. Latent growth models and standard regression techniques were used to examine the rate of cognitive decline in four cognitive measures while controlling for health status and sex. A delayed start model was examined by incorporating interaction effects in a regression model.Results. Neither the latent growth models nor the regression techniques revealed a slower rate of decline for the more highly educated. The proportion of the highly educated showing no change was no larger than the proportion of the less well educated. There were no significant age by education interaction effects, no chronologically later accelerations in the rate of change as a function of education, and no differences in rate of decline between the first measurement interval and the second.Conclusions. Education may not protect against cognitive decline although it is associated with long-term individual differences in level of functioning. The discrepancy between our study and others may be attributable to attrition effects, follow-up length, sample age, scaling artefacts and negative publication bias. Most importantly, practice effects may favour the better educated and hence account for the supposed protective effect in many longitudinal studies of cognitive change.

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A Study on the Latent Growth Models of the Professional Baseball Team’s Winning Rates and the Value of the Companies

Korean Journal of Sports Science ◽

10.35159/kjss.2020.02.29.1.399 ◽

2020 ◽

Vol 29 (1) ◽

pp. 399-408

Author(s):

Min-Uk Kang ◽

Soon-Young Kim

Keyword(s):

Growth Models ◽

Professional Baseball ◽

Latent Growth ◽

Latent Growth Models

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Nuances in Alzheimer’s Genetic Risk Reveal Differential Predictions of Non-demented Memory Aging Trajectories: Selective Patterns by APOE Genotype and Sex

Current Alzheimer Research ◽

10.2174/1567205016666190315094452 ◽

2019 ◽

Vol 16 (4) ◽

pp. 302-315 ◽

Cited By ~ 1

Author(s):

G. Peggy McFall ◽

Lars Bäckman ◽

Roger A. Dixon

Keyword(s):

Genetic Risk ◽

Growth Models ◽

Memory Performance ◽

Apoe Genotype ◽

Cognitively Impaired ◽

Latent Growth ◽

Latent Growth Models ◽

Selective Protection ◽

Underlying Mechanisms ◽

Apoe Genotypes

Background: Apolipoprotein E (APOE) is a prominent genetic risk factor for Alzheimer’s disease (AD) and a frequent target for associations with non-demented and cognitively impaired aging. APOE offers a unique opportunity to evaluate two dichotomous comparisons and selected gradations of APOE risk. Some evidence suggests that APOE effects may differ by sex and emerge especially in interaction with other AD-related biomarkers (e.g., vascular health). Methods: Longitudinal trajectories of non-demented adults (n = 632, 67% female, Mage = 68.9) populated a 40-year band of aging. Focusing on memory performance and individualized memory trajectories, a sequence of latent growth models was tested for predictions of (moderation between) APOE and pulse pressure (PP) as stratified by sex. The analyses (1) established robust benchmark PP effects on memory trajectories, (2) compared predictions of alternative dichotomous groupings (ε4- vs ε4+, ε2- vs ε2+), and (3) examined precision-based predictions by disaggregated APOE genotypes. Results: Healthier (lower) PP was associated with better memory performance and less decline. Therefore, all subsequent analyses were conducted in the interactive context of PP effects and sex stratification. The ε4-based dichotomization produced no differential genetic predictions. The ε2-based analyses showed sex differences, including selective protection for ε2-positive females. Exploratory follow-up disaggregated APOE genotype analyses suggested selective ε2 protection effects for both homozygotic and heterozygotic females. Conclusion: Precision analyses of AD genetic risk will advance the understanding of underlying mechanisms and improve personalized implementation of interventions.

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