Constrained and unconstrained multivariate normal finite mixture modeling of Piagetian data
Constrained and unconstrained multivariate normal finite mixture modeling of Piagetian data
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DOI：
10.1207/s15327906mbr3901_3
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发表时间：
2004-01-01
影响因子：
3.8
通讯作者：
van der Maas, HLJ
中科院分区：
文献类型：
--
作者：
Dolan, CV;Jansen, BRJ;van der Maas, HLJ
我们提出的多元正态混合模型的皮亚杰数据的结果。样本由101名儿童，谁进行了（伪）保护计算机任务的四个场合。我们拟合了横截面混合模型和基于马尔可夫过渡模型的纵向模型。皮亚杰的认知发展理论为混合物中成分的数量和解释提供了强有力的基础。皮亚杰发展的大多数研究都是基于离散响应的混合模型。目前的研究结果表明，正常的混合建模是一个有用的方法，当响应是连续的，近似正常的组件内。多元正态混合建模的优点是可以对分量内的协方差结构进行建模。一般来说，结果是一致的存在不同的模式的响应。这为分阶段发展的假设提供了支持。
We present the results of multivariate normal mixture modeling of Piagetian data. The sample consists of 101 children, who carried out a (pseudo-)conservation computer task on four occasions. We fitted both cross-sectional mixture models, and longitudinal models based on a Markovian transition model. Piagetian theory of cognitive development provides a strong basis for the number and interpretation of the components in the mixtures. Most studies of Piagetian development have been based on mixture modeling of discrete responses. The present results show that normal mixture modeling is a useful approach, when responses are continuous and approximately normal within the components. Multivariate normal mixture modeling has the advantage that the covariance structure within the components may be modeled. Generally the results are consistent with the presence of distinct modes of responding. This provides support for the hypothesis of stage-wise development.