对扫描电镜的思考

IF 2.8 4区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Data Base for Advances in Information Systems Pub Date : 2021-12-09 DOI:10.1145/3505639.3505646
Joseph F. Hair
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引用次数: 6

摘要

近40年来,结构方程模型(SEM)一直是社会科学中评估测量和结构关系的首选统计工具。在最初的30年里,几乎所有扫描电镜的应用都使用了众所周知的基于协方差的扫描电镜。但在过去十年中,一种替代的结构方程建模方法——基于复合材料的扫描电镜(SEM)得到了越来越多的应用。事实上,相当多的社会科学学者认为基于复合的SEM是结构方程建模应用的选择方法。在本文中,我概述了扫描电镜的演变,从早期基于因子的扫描电镜是主导方法到近年来基于复合的方法变得更加普遍。我还总结了几个相关的基于复合的主题,包括基于复合的SEM,验证性复合分析(CCA)和广义结构化成分分析(GSCA)的新方法的出现。在最后一节中,我提出了一些关于基于复合材料的扫描电镜方法的当前发展和未来机会的观察。
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Reflections on SEM
For almost 40 years structural equation modeling (SEM) has been the statistical tool of choice for the assessing measurement and structural relationships in the social sciences. During the initial 30 years almost all applications of SEM utilized what has become known as covariance-based SEM. But in the past ten years an alternative structural equation modeling method, composite-based SEM, has increasingly been applied. In fact, a substantial number of social sciences scholars consider composite-based SEM the method of choice for structural equation modeling applications. In this paper, I provide an overview of the evolution of SEM, from the early years when factor-based SEM was the dominant method to the more recent years as composite-based methods have become much more prevalent. I also summarize several relevant composite-based topics including the emergence of composite-based SEM, confirmatory composite analysis (CCA), and a new method of generalized structured component analysis (GSCA). In the final section I propose some observations about current developments and future opportunities for composite-based SEM methods.
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来源期刊
Data Base for Advances in Information Systems
Data Base for Advances in Information Systems INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.60
自引率
7.10%
发文量
18
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