A method for modeling the intrinsic dynamics of intraindividual variability: Recovering the parameters of simulated oscillators in multi-wave panel data
A method for modeling the intrinsic dynamics of intraindividual variability: Recovering the parameters of simulated oscillators in multi-wave panel data
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DOI：
10.1207/s15327906mbr3701_06
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发表时间：
2002-01-01
影响因子：
3.8
通讯作者：
Nesselroade, JR
中科院分区：
文献类型：
--
作者：
Boker, SM;Nesselroade, JR
将微分方程拟合到多波面板数据的简单方法在从底层连续模型中恢复参数方面表现得非常好，只需三波数据。通过测试这些技术从两个微分方程模拟系统生成的数据恢复参数的行为，检验了两种将内在动力学模型拟合到个体变异性数据的技术。每个模拟数据集包含 100 个“受试者”，每个受试者仅在三个时间点进行测量。受试者数据的一阶和二阶导数的局部线性近似准确地恢复了每个模拟的真实参数。用于估计一阶和二阶导数的状态空间嵌入技术也无法恢复参数。该模型的最佳采样间隔可以估计为多个 RI 首先接近其渐近值的间隔。
A simple method for fitting differential equations to multi-wave panel data performs remarkably well in recovering parameters from underlying continuous models with as few as three waves of data. Two techniques for fitting models of intrinsic dynamics to intraindividual variability data are examined by testing these techniques' behavior in recovering the parameters from data generated by two simulated systems of differential equations. Each simulated data set contains 100 "subjects" each of whom are measured at only three points in time. A local linear approximation of the first and second derivatives of the subject's data accurately recovers the true parameters of each simulation. A state-space embedding technique for estimating the first and second derivatives does not recover the parameters as well. An optimum sampling interval can be estimated for this model as that interval at which multiple RI first nears its asymptotic value.