计算机科学
数学
路径(计算)
计量经济学
统计
程序设计语言
作者
Michel Tenenhaus,Vincenzo Esposito Vinzi,Yves-Marie Chatelin,C. di Lauro
标识
DOI:10.1016/j.csda.2004.03.005
摘要
A presentation of the Partial Least Squares approach to Structural Equation Modeling (or PLS Path Modeling) is given together with a discussion of its extensions. This approach is compared with the estimation of Structural Equation Modeling by means of maximum likelihood (SEM-ML). Notwithstanding, this approach still shows some weaknesses. In this respect, some new improvements are proposed. Furthermore, PLS path modeling can be used for analyzing multiple tables so as to be related to more classical data analysis methods used in this field. Finally, a complete treatment of a real example is shown through the available software.
科研通智能强力驱动
Strongly Powered by AbleSci AI