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. Author manuscript; available in PMC: 2020 Jun 1.
Published in final edited form as: Dev Psychol. 2019 Mar 4;55(6):1338–1352. doi: 10.1037/dev0000716

Table 4.

Parameter estimates of LCS Model 4

Ctx = Cortical Thickness Ctx = Cortical Surface Area
Parameter Estimate SE p Stzd. factor loading / Correlation Estimate SE p Stzd. factor loading / Correlation
Factor λ Block Designc 1.000 fixed .781b 1.000 fixed .783b
loadingsa λ Matricesb .685 .042 .000 .713b .685 .042 .000 .715b
(g measured by) λ Similarities .945 .028 .000 .892b .945 .028 .000 .893b
λ Vocabulary 1.014 .028 .000 .924b 1.014 .028 .000 .925b
Intercepts τ g0 .000 fixed .000 fixed
τ gs .742 .029 .000 .752 .026 .000
τ Ctx0 .759 .078 .000 .138 .092 .132
τ CtxS −.052 .078 .505 .209 .046 .000
Regressions δ Age → g0 .145 .013 .000 .572 .147 .013 .000 .582
δ ln(Age) → g0 .304 .041 .000 .370 .296 .041 .000 .360
δ Age → Ctx0 −.170 .027 .000 −.694 −.072 .032 .026 −.260
δ ln(Age) → Ctx0 .084 .093 .367 .106 .238 .110 .031 .264
δ Age → gs −.057 .009 .000 −.938 −.062 .010 .000 −1.060
δ ln(Age) → gs −.014 .023 .554 −.069 .013 .027 .625 .068
δ Age → CtxS .028 .025 .262 1.230 −.003 .010 .787 −.083
δ ln(Age) → Ctxs −.143 .068 .034 −1.916 −.100 .045 .025 −.926
Determinants β g → Δg .051 .033 .129 .037 .039 .352
of change in g ϕ Δg → Δg −.208 .065 .001 −.526 .130 .000
γ Ctx → Δg .003 .017 .836 .014 .013 .293
ξ ΔCtx → Δg .330 .119 .005 1.016 .471 .031
Determinants β Ctx → ΔCtx .000 .047 .997 −.014 .014 .334
of change in Ctx ϕ ΔCtx → ΔCtx −.880 .221 .000 −.260 .586 .658
γ g → ΔCtx −.127 .094 .173 .014 .043 .741
ξ Δg → ΔCtx −.331 .139 .017 −.199 .154 .197
Latent residual σ g0-Ctx0 .044 .018 .015 .173 .075 .022 .001 .211
variances-covar. σ2 g0 .131 .013 .000 .160 .131 .014 .000 .160
σ2 Ctx0 .490 .051 .000 .638 .971 .077 .000 .985

Note: n=430. Statistically significant parameters of interest are shaded (α=.05).

“a”

= factor loadings invariant across occasions (except for Matrices).

“b”

= mean across the three waves.

“c”

= parameter fixed.

“ln(Age)” = Natural logarithm of age, capturing non-linear influences. Intercepts for the observed indicators and residual variances are not shown. Standardized values for the intercepts and dynamic parameters are not interpretable, and therefore not shown.