Supplementary Table 1 shows the proportion of missing data by variable stratified by class and computed maximum difference between classes and final predictors within the final backward stepwise multi

Figshare2026-01-07 更新20

Summary statistics from the latent class growth analysis reveals six trajectory model is optimal for explaining heterogeneity in cognitive scores.

潜在类别增长模型

认知发展轨迹

Summary statistics from the latent class growth analysis reveals six trajectory model is optimal for explaining heterogeneity in cognitive scores.

Figshare2017-06-08 更新30

Fit indices for latent class growth models for anxiety, affective problems, and oppositional-defiant problems.

潜在类别增长模型

心理行为问题发展轨迹

Fit indices for latent class growth models for anxiety, affective problems, and oppositional-defiant problems.

NIAID Data Ecosystem20

Parameter estimates for the quadratic LCM for females.

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