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An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences
An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences
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An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences
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An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences
An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences
Journal Article

An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences

2018
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Overview
This paper is a tribute to researchers who have significantly contributed to improving and advancing structural equation modeling (SEM). It is, therefore, a brief overview of SEM and presents its beginnings, historical development, its usefulness in the social sciences and the statistical and philosophical (theoretical) controversies which have often appeared in the literature pertaining to SEM. Having described the essence of SEM in the context of causal analysis, the author discusses the years of the development of structural modeling as the consequence of many researchers’ systematically growing needs (in particular in the social sciences) who strove to effectively understand the structure and interactions of latent phenomena. The early beginnings of SEM models were related to the work of Spearman and Wright, and to that of other prominent researchers who contributed to SEM development. The importance and predominance of theoretical assumptions over technical issues for the successful construction of SEM models are also described. Then, controversies regarding the use of SEM in the social sciences are presented. Finally, the opportunities and threats of this type of analytical strategy as well as selected areas of SEM applications in the social sciences are discussed.