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Structure and correlates of cognitive aging in a narrow age cohort.

Tucker-Drob EM, Briley DA, Starr JM, Deary IJ - Psychol Aging (2014)

Bottom Line: However, previous studies have typically been conducted in age-heterogeneous samples over longitudinal time lags of 6 or more years, and have failed to consider whether results are robust to a comprehensive set of controls.We fit multivariate latent difference score models to factors representing visuospatial ability, processing speed, memory, and crystallized ability.Changes were moderately interrelated, with a general factor of change accounting for 47% of the variance in changes across domains.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology.

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Related in: MedlinePlus

Path diagram for a single factor (y) measured by three indicators (Ya, Yb, and Yc) at baseline [0] and follow-up [1] occasions.
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Related In: Results  -  Collection

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fig1: Path diagram for a single factor (y) measured by three indicators (Ya, Yb, and Yc) at baseline [0] and follow-up [1] occasions.

Mentions: We made use of a latent difference score modeling approach (McArdle, 2009), a univariate version of which is represented as a path diagram in Figure 1. The measurement portion of this approach specifies a latent factor, y, measured by multiple tests (e.g., Ya, Yb, and Yc) on two occasions separated in time. The brackets [0] and [1] denote baseline and follow-up occasions, respectively. Each test is specified to load on the occasion-specific latent variable with a loading (λ), and each test is allowed to have an intercept (υ) and a residual variance (σ2). Cross-time residual autocorrelations (σ12) are allowed for each test. The baseline factor is set to the z-metric (M = 0, SD = 1), and the mean and the variance of the difference score can therefore be interpreted relative to this metric.


Structure and correlates of cognitive aging in a narrow age cohort.

Tucker-Drob EM, Briley DA, Starr JM, Deary IJ - Psychol Aging (2014)

Path diagram for a single factor (y) measured by three indicators (Ya, Yb, and Yc) at baseline [0] and follow-up [1] occasions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4067230&req=5

fig1: Path diagram for a single factor (y) measured by three indicators (Ya, Yb, and Yc) at baseline [0] and follow-up [1] occasions.
Mentions: We made use of a latent difference score modeling approach (McArdle, 2009), a univariate version of which is represented as a path diagram in Figure 1. The measurement portion of this approach specifies a latent factor, y, measured by multiple tests (e.g., Ya, Yb, and Yc) on two occasions separated in time. The brackets [0] and [1] denote baseline and follow-up occasions, respectively. Each test is specified to load on the occasion-specific latent variable with a loading (λ), and each test is allowed to have an intercept (υ) and a residual variance (σ2). Cross-time residual autocorrelations (σ12) are allowed for each test. The baseline factor is set to the z-metric (M = 0, SD = 1), and the mean and the variance of the difference score can therefore be interpreted relative to this metric.

Bottom Line: However, previous studies have typically been conducted in age-heterogeneous samples over longitudinal time lags of 6 or more years, and have failed to consider whether results are robust to a comprehensive set of controls.We fit multivariate latent difference score models to factors representing visuospatial ability, processing speed, memory, and crystallized ability.Changes were moderately interrelated, with a general factor of change accounting for 47% of the variance in changes across domains.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology.

Show MeSH
Related in: MedlinePlus