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. 2022 Feb 2;8(5):eabj2422. doi: 10.1126/sciadv.abj2422

Table 2. Parameter estimates from step 1 and step 2 “factor of curves” models in BETULA.

ρFi,Fsa = 0.233 (P = 0.063), ρFi,Fqa = −0.654 (P < 0.001), and ρFs,Fqa = −0.121 (P = 0.705). The variance of Fi, Fs, and Fq were fixed to 1.0 to define the metrics of the latent growth factors. We specified age-based growth curve modeling, such that the basis coefficients for each of the five slopes was set to the age in quarter centuries of individual n at each assessment on variable w, centered at 50 years. Each of the four cognitive outcomes was standardized by subtracting the mean of all datapoints at the baseline occasion and dividing by the SD of the age and age-squared residuals of all the datapoints at baseline.

Cognitive
domain
Latent variable means (SE) Unstandardized
loadings (SE)
Standardized
loadings
Residual variances and covariances (SE)
μr μi μs μq Fi Fs Fq Fi F s Fq σ2e[t] σ2ui σ2us σ2uq σui,us σui,uq σus,uq
Gv* 0.127
(0.016)
0.544
(0.022)
−0.871
(0.042)
−0.525
(0.033)
0.599
(0.032)
0.298
(0.072)
0.284
(0.068)
0.643
(0.03)
0.851
(0.088)
0.825
(0.127)
0.269
(0.007)
0.511
(0.036)
0.034
(0.02)
0.038
(0.029)
−0.02
(0.025)
−0.107
(0.038)
−0.01
(0.031)
Gm* 0.195
(0.02)
0.577
(0.02)
−0.744
(0.041)
−0.682
(0.035)
0.477
(0.029)
0.312
(0.066)
0.285
(0.07)
0.711
(0.036)
0.748
(0.098)
0.931
(0.034)
0.517
(0.012)
0.223
(0.028)
0.077
(0.032)
0.013
(0.003)
0.057
(0.022)
−0.035
(0.043)
−0.03
(0.031)
Gs* 0.185
(0.018)
0.925
(0.027)
−0.936
(0.058)
−0.85
(0.043)
0.65
(0.035)
0.563
(0.08)
0.346
(0.125)
0.758
(0.033)
0.819
(0.059)
0.729
(0.136)
0.21
(0.019)
0.314
(0.04)
0.156
(0.053)
0.106
(0.026)
0.011
(0.034)
−0.076
(0.053)
−0.125
(0.035)
G c 0.123
(0.013)
0.319
(0.016)
−0.033
(0.03)
−0.58
(0.028)
0.623
(0.025)
0.425
(0.029)
0.258
(0.05)
0.763
(0.021)
0.859
(0.024)
0.461
(0.097)
0.162
(0.006)
0.278
(0.025)
0.064
(0.012)
0.247
(0.071)
0.106
(0.029)
−0.078
(0.033)
−0.059
(0.056)

*First step: unconstrained factor of curves model excluding Gc.

†Second step: constrained factor of curves model including Gc.