结构方程建模
路径分析(统计学)
调解
过程(计算)
偏最小二乘回归
通径系数
计量经济学
潜变量
回归分析
宏
计算机科学
心理学
工业工程
数学
机器学习
工程类
政治学
操作系统
程序设计语言
法学
作者
Andrew F. Hayes,Amanda Kay Montoya,Nicholas Rockwood
标识
DOI:10.1016/j.ausmj.2017.02.001
摘要
Marketing, consumer, and organizational behavior researchers interested in studying the mechanisms by which effects operate and the conditions that enhance or inhibit such effects often rely on statistical mediation and conditional process analysis (also known as the analysis of “moderated mediation”). Model estimation is typically undertaken with ordinary least squares regression-based path analysis, such as implemented in the popular PROCESS macro for SPSS and SAS ( Hayes, 2013 ), or using a structural equation modeling program. In this paper we answer a few frequently-asked questions about the difference between PROCESS and structural equation modeling and show by way of example that, for observed variable models, the choice of which to use is inconsequential, as the results are largely identical. We end by discussing considerations to ponder when making the choice between PROCESS and structural equation modeling.
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