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Bayesian structural equation modelling tutorial for novice management researchers

机译：新手管理研究人员的贝叶斯结构方程建模教程

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Purpose - This paper aims to popularize the Bayesian methods among novice management researchers. The paper interprets the results of Bayesian method of confirmatory factor analysis (CFA), structural equation modelling (SEM), mediation and moderation analysis, with the intention that the novice researchers will apply this method in their research. The paper made an attempt in discussing various complex mathematical concepts such as Markov Chain Monte Carlo, Bayes factor, Bayesian information criterion and deviance information criterion (DIC), etc. in a lucid manner. Design/methodology/approach - Data collected from 172 pharmaceutical sales representatives were used. The study will help the management researchers to perform Bayesian CFA, Bayesian SEM, Bayesian moderation analysis and Bayesian mediation analysis using SPSS AMOS software. Findings - The interpretation of the results of Bayesian CFA, Bayesian SEM and Bayesian mediation analysis were discussed. Practical implications - The management scholars are non-statisticians and are not much aware of the benefits offered by Bayesian methods. Hitherto, the management scholars use predominantly traditional SEM in validating their models empirically, and this study will give an exposure to "Bayesian statistics" that has practical advantages. Originality/value - This is one paper, which discusses the following four concepts: Bayesian method of CFA SEM, mediation and moderation analysis.
机译：目的-本文旨在在新手管理研究人员中推广贝叶斯方法。本文解释了确定性因子分析（CFA），结构方程模型（SEM），中介和调节分析的贝叶斯方法的结果，旨在使新手研究人员将这种方法应用于他们的研究。本文试图以清晰的方式讨论各种复杂的数学概念，例如马尔可夫链蒙特卡洛，贝叶斯因子，贝叶斯信息准则和偏差信息准则（DIC）等。设计/方法/方法-使用从172个药品销售代表处收集的数据。该研究将帮助管理研究人员使用SPSS AMOS软件执行贝叶斯CFA，贝叶斯SEM，贝叶斯中度分析和贝叶斯中介分析。调查结果-讨论了贝叶斯CFA，贝叶斯SEM和贝叶斯调解分析结果的解释。实际意义-管理学者不是统计学家，对贝叶斯方法的好处并不十分了解。迄今为止，管理学者主要使用传统的SEM来凭经验验证其模型，本研究将对具有实际优势的“贝叶斯统计”进行一次探讨。创意/价值-这是一篇论文，讨论了以下四个概念：CFA SEM的贝叶斯方法，中介和调节分析。

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