Principles and Practice of Structural Equation Modeling, 4th edition Rex B. Kline New York: The Guilford Press 2016 ISBN 978-1-4625-2334-4 Softcover, US$65, 534 pp. Kline’s fourth edition is reasonably strong but improvable. The text aims to introduce newcomers to fundamental structural equation modeling (SEM) principles, but tends to confuse “Principles” with “Rules.” Rules having insufficient grounding in principles leave readers ill-prepared for understanding and responding to changes in previously traditional “rules”—such as those concerning model testing, and latents having single indicators. SEM’s foundations would be clearer if Kline began by presenting structural equation models as striving to represent causal effects—a commitment that differentiates structural equation models from regression and encourages model testing. I begin this review by summarizing the covariance/correlation implications of three simple causal structures, which pinpoints multiple text improvements and underpins the discussions of measurement and model testing that follow. Causal structuring also grounds my later comments regarding modelling means/intercepts and interactions. A file of Supplementary Sections expands on several points and lists multiple editorial corrections you might pencil into your copy of Kline’s text.

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Rex B. Kline 的结构方程建模原理与实践：鼓励第五版的评论文章

结构方程建模的原理与实践，第 4 版 Rex B. Kline 纽约：吉尔福德出版社 2016 ISBN 978-1-4625-2334-4 平装，65 美元，534 页。 Kline 的第四版相当强大，但仍需改进。本书旨在向新手介绍基本的结构方程模型 (SEM) 原理，但往往会将“原理”与“规则”混淆。原则基础不充分的规则让读者无法理解和应对以前传统“规则”的变化——例如那些涉及模型测试的规则，以及具有单一指标的潜在规则。如果 Kline 开始将结构方程模型呈现为努力表示因果效应——这一承诺将结构方程模型与回归区分开来并鼓励模型测试，那么 SEM 的基础将会更加清晰。我通过总结三个简单因果结构的协方差/相关性含义开始这篇评论，它指出了多个文本改进，并支持了随后对测量和模型测试的讨论。因果结构也是我后来关于建模手段/拦截和相互作用的评论的基础。补充部分文件扩展了几个点，并列出了您可能会在克莱恩文本副本中写入的多个编辑更正。