标题： 婴儿期生长与学龄前认知表现的关联：函数数据分析方法 显示英文标题

标题： Associating Growth in Infancy and Cognitive Performance in Early Childhood: A functional data analysis approach

摘要： 身体生长特征可以由连续函数自然表示。 在大量婴儿生长模式的数据集中，我们开发了一种实用的方法来推断生长轨迹与早期儿童智商表现之间的统计关联。 本研究的主要目标是展示如何评估身体生长曲线，并检测特定的婴儿生长模式是否与后期年龄智商（全量表WASI得分）的差异有关，采用半参数函数响应模型。 此外，我们调查了不同生长测量值之间的关联，包括它们彼此之间的互相关性、与后期智商的相关性以及它们随时间变化的动态。 该分析框架可以非参数化地轻松整合或学习人口信息，从而使先前的人口图表部分冗余。 显示英文摘要

摘要： Physical growth traits can be naturally represented by continuous functions. In a large dataset of infancy growth patterns, we develop a practical approach to infer statistical associations between growth-trajectories and IQ performance in early childhood. The main objective of this study is to show how to assess physical growth curves and detect if particular infancy growth patterns are associated with differences in IQ (Full-scale WASI scores) in later ages using a semi-parametric functional response model. Additionally, we investigate the association between different growth measurements in terms of their cross-correlation with each other, their correlation with later IQ, as well as their time-varying dynamics. This analysis framework can easily incorporate or learn population information in a non-parametric way, rendering the existence of prior population charts partially redundant.