Structured latent curve models for the study of change in multivariate repeated measures
Structured latent curve models for the study of change in multivariate repeated measures
复制标题
DOI：
10.1037/1082-989x.9.3.334
复制
发表时间：
2004-09-01
影响因子：
7
通讯作者：
Blozis, SA
中科院分区：
文献类型：
--
作者：
Blozis, SA
本文考虑了一个多重复测量的结构化潜曲线模型。在结构化潜曲线模型中，平滑的非线性函数表征平均响应。关于均值函数采用的一阶泰勒多项式定义了限制因子矩阵的元素，该限制因子矩阵可以包括非线性进入的参数。与因子得分类似，随机系数与因子矩阵相结合，以产生不需要遵循与平均曲线相同的形式的个体潜曲线。在这里，在多个重复测量的变化特征之间的关联进行了研究。一个因素分析模型的协变量包括作为一种手段，有关潜在的协变量的因素特征的变化，在不同的重复测量。提供了一个例子。
This article considers a structured latent curve model for multiple repeated measures. In a structured latent curve model, a smooth nonlinear function characterizes the mean response. A first-order Taylor polynomial taken with regard to the mean function defines elements of a restricted factor matrix that may include parameters that enter nonlinearly. Similar to factor scores, random coefficients are combined with the factor matrix to produce individual latent curves that need not follow the same form as the mean curve. Here the associations between change characteristics in multiple repeated measures are studied. A factor analysis model for covariates is included as a means of relating latent covariates to the factors characterizing change in different repeated measures. An example is provided.