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The time has come: Toward Bayesian SEM estimation in tourism research

机译:时机已到:在旅游研究中寻求贝叶斯SEM估计

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While the Bayesian SEM approach is now receiving a strong attention in the literature, tourism studies still heavily rely on the covariance-based approach for SEM estimation. In a recent special issue dedicated to the topic, Zyphur and Oswald (2013) used the term "Bayesian revolution" to describe the rapid growth of the Bayesian approach across multiple social science disciplines. The method introduces several advantages that make SEM estimation more flexible and powerful. We aim in this paper to introduce tourism researchers to the power of the Bayesian approach and discuss its unique advantages over the covariance-based approach. We provide first some foundations of Bayesian estimation and inference. We then present an illustration of the method using a tourism application. The paper also conducts a Monte Carlo simulation to illustrate the performance of the Bayesian approach in small samples and discuss several complicated SEM contexts where the Bayesian approach provides unique advantages. (C) 2017 Elsevier Ltd. All rights reserved.
机译:尽管贝叶斯SEM方法现在在文献中受到了广泛关注,但旅游业研究仍然严重依赖基于协方差的方法进行SEM估计。 Zyphur和Oswald(2013)在最近专门针对该主题的专刊中使用“贝叶斯革命”一词来描述贝叶斯方法在多个社会科学学科中的快速发展。该方法引入了一些优点,这些优点使SEM估算更加灵活和强大。在本文中,我们旨在向旅游研究人员介绍贝叶斯方法的强大功能,并讨论其在基于协方差的方法上的独特优势。我们首先提供贝叶斯估计和推断的一些基础。然后,我们使用旅游应用程序介绍该方法。本文还进行了蒙特卡洛模拟,以说明小样本中的贝叶斯方法的性能,并讨论了贝叶斯方法提供独特优势的几种复杂的SEM环境。 (C)2017 Elsevier Ltd.保留所有权利。

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