Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts.
Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts.
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DOI：
10.1177/0962280213503925
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发表时间：
2016-10
影响因子：
2.3
通讯作者：
Lawlor DA
中科院分区：
文献类型：
--
作者：
Howe LD;Tilling K;Matijasevich A;Petherick ES;Santos AC;Fairley L;Wright J;Santos IS;Barros AJ;Martin RM;Kramer MS;Bogdanovich N;Matush L;Barros H;Lawlor DA
儿童生长是医学研究的兴趣，关注健康生长和发育变化的决定因素和后果。线性样条多层次模型是一种有用的方法，用于推导个体生长汇总指标，它克服了几个数据问题（重复测量的共线性，要求所有个体在相同年龄进行测量，以及由于缺失数据而产生的偏倚）。在这里，我们概述了这种方法的应用，以模拟个人的长度/身高和体重的轨迹，从不同世代和不同地理区域的不同经济发展水平的五个队列的例子。我们描述了每个队列内的数据的独特功能，有影响的线性样条多水平模型的应用，例如，在密度和个体间的差异测量场合，和不同的测量误差的多个测量源的差异。在提供了示例Stata语法和建议的工作流程的线性样条多级模型的实施后，我们结束了与其他增长建模方法，如分数多项式，更复杂的样条函数和其他非线性模型相比，线性样条方法的优点和缺点的讨论。
Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models.
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影响因子：
7.7
作者：
Cole TJ;Donaldson MD;Ben-Shlomo Y
通讯作者：
Ben-Shlomo Y
影响因子：
158.5
作者：
Barker, DJP;Osmond, C;Eriksson, JG
通讯作者：
Eriksson, JG
影响因子：
158.5
作者：
Baker, Jennifer L.;Olsen, Lina W.;Sorensen, Thorkild I. A.
通讯作者：
Sorensen, Thorkild I. A.
影响因子：
6.3
作者：
Howe, Laura D.;Tilling, Kate;Lawlor, Debbie A.
通讯作者：
Lawlor, Debbie A.
影响因子：
4.2
作者：
Cole, TJ
通讯作者：
Cole, TJ