Tutorial in Biostatistics: Evaluating the impact of 'critical periods' in longitudinal studies of growth using piecewise mixed effects models
Tutorial in Biostatistics: Evaluating the impact of 'critical periods' in longitudinal studies of growth using piecewise mixed effects models
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DOI：
10.1093/ije/30.6.1332
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发表时间：
2001-12-01
影响因子：
7.7
通讯作者：
Laird, NM
中科院分区：
文献类型：
--
作者：
Naumova, EN;Must, A;Laird, NM
调制解调器多元方法的最新发展为应用研究人员提供了解决许多重要的研究问题的方法，这些研究与重复测量有关个人收集的数据随着时间的流逝而产生的许多重要研究问题。应用研究的一个这样的领域的重点是研究与人类发展中某些事件或关键时期相关的变化。本教程与使用通用线性混合模型的使用用于对相关数据的回归分析，并具有时间的两件式线性函数到事前和事后趋势。该模型假设连续结果与一组解释变量线性相关，但是事件后的趋势与之前的趋势不同。可以使用纵向数据的分段线性随机效应模型来完成此任务，其中响应取决于事件的时间。一个详细的示例，该详细示例将使用对前瞻性研究的数据来介绍初潮对体内脂肪积聚变化的影响，从而介绍每年大约10岁到初潮后4年，每年162个女孩。
Recent developments in modem multivariate methods provide applied researchers with the means to address many important research questions that arise in studies with repeated measures data collected on individuals over time. One such area of applied research is focused on studying change associated with some event or critical period in human development.This tutorial deals with the use of the general linear mixed model for regression analysis of correlated data with a two-piece linear function of time corresponding to the pre- and post-event trends. The model assumes a continuous outcome is linearly related to a set of explanatory variables, but allows for the trend after the event to be different from the trend before it. This task can be accomplished using a piecewise linear random effects model for longitudinal data where the response depends upon time of the event.A detailed example that examines the influence of menarche on changes in body fat accretion will be presented using data from a prospective study of 162 girls measured annually from approximately age 10 until 4 years post menarche.