利用随机变点和异质随机效应对生长曲线进行多类分类
Multiclass classification of growth curves using random change points and heterogeneous random effects
摘要：
儿童发育迟缓是中低收入国家普遍存在的一个营养问题;通常定义为与同龄和同性别的健康参考人群相比，发育速度较慢。由于步履蹒跚与身体、智力和经济生产力潜力下降密切相关，因此识别步履蹒跚的儿童并能够描述不同的生长模式非常重要，以便设计和实施有针对性的治疗。我们引入了一个多类分类模型的增长轨迹，灵活地扩展了目前的分类方法称为断棒模型，这是一个分段的线性模型，在固定的节点位置休息。使用混合分布的随机效应捕获儿童生长模式中的异质性，由此混合成分确定儿童分组的分类。混合物分布使用Dirichlet过程先验建模，这避免了选择混合物组分的“真实”数量的需要，并允许由数据的复杂性驱动。由于儿童在生长阶段的开始有个体差异，我们引入儿童特定的随机变化点。仿真结果表明，随机变点模型优于断棒模型，因为它对节点位置的限制较少。我们说明了我们的模型上的纵向出生队列健康出生，生长和发展的知识整合项目由比尔和梅林达盖茨基金会资助。分析表明，人口中有9个儿童分组，从出生到一岁，表现出不同的蹒跚趋势。
英文摘要：
Faltering growth among children is a nutritional problem prevalent in low to medium income countries; it is generally defined as a slower rate of growth compared to a reference healthy population of the same age and gender. As faltering is closely associated with reduced physical, intellectual and economic productivity potential, it is important to identify faltered children and be able to characterise different growth patterns so that targeted treatments can be designed and administered. We introduce a multiclass classification model for growth trajectory that flexibly extends a current classification approach called the broken stick model, which is a piecewise linear model with breaks at fixed knot locations. Heterogeneity in growth patterns among children is captured using mixture distributed random effects, whereby the mixture components determine the classification of children into subgroups. The mixture distribution is modelled using a Dirichlet process prior, which avoids the need to choose the "true" number of mixture components, and allows this to be driven by the complexity of the data. Because children have individual differences in the onset of growth stages, we introduce child-specific random change points. Simulation results show that the random change point model outperforms the broken stick model because it has fewer restrictions on knot locations. We illustrate our model on a longitudinal birth cohort from the Healthy Birth, Growth and Development knowledge integration project funded by the Bill and Melinda Gates Foundation. Analysis reveals 9 subgroups of children within the population which exhibit varying faltering trends between birth and age one.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
