文章基本信息

标题：Assessing item contribution on unobservable variables’ measures with hierarchical data
其他标题：Assessing item contribution on unobservable variables’ measures with hierarchical data
作者：Vezzoli, Marika ; Manisera, Marica
期刊名称：Electronic Journal of Applied Statistical Analysis
电子版ISSN：2070-5948
出版年度：2012
卷号：5
期号：3
页码：314-319
DOI：10.1285/i20705948v5n3p314
语种：English
出版社：University of Salento
摘要：This paper aims at measuring the contribution of each item used to construct composite indicators of unobservable variables when data come from multi-item scales and have a hierarchical structure. To this end, we combine the MultiLevel NonLinear Principal Components Analysis with the MultiLevel Mean Decrease in Accuracy. The first algorithm is used to realize a composite indicator of the latent variable, while the second is a variable importance measure, introduced in the context of CRAGGING, which is an ensemble method able to deal with hierarchical data. The two techniques are combined in such an extent to take account of the data structure, thus offering a new way to assess the items' contribution on the hierarchical-based unobservable variables' measure.
关键词：Unobservable Variables; Variable Importance Measures; Multilevel; Nonlinear Principal Components Analysis; CRAGGING