社会与行为研究中的机器学习综述(社会科学方法论)。文/ Ross Jacobucci, Kevin J. Grimm，张志勇。纽约:吉尔福德出版社(2023)，416页，93.00美元(精装本)，ISBN: 9781462552931。$62.00(平装本)，ISBN: 9781462552924。62.00美元(PDF)。
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引用次数: 0
摘要
点击放大图片点击缩小图片致谢感谢印尼财政部印尼教育捐赠基金(ldp)为本文的发表和作者的研究生学业提供资金支持。披露声明作者报告无潜在利益冲突。本研究由Lembaga Pengelola Dana Pendidikan资助。
Review of Machine Learning for Social and Behavioral Research (Methodology in the Social Sciences)Review of Machine Learning for Social and Behavioral Research (Methodology in the Social Sciences) . By Ross Jacobucci, Kevin J. Grimm, Zhiyong Zhang. New York, NY: The Guilford Press, (2023), 416 pp. $93.00 (Hardback), ISBN: 9781462552931. $62.00 (Paperback), ISBN: 9781462552924. $62.00 (PDF).
Click to increase image sizeClick to decrease image size AcknowledgmentsThe authors express their gratitude to the Indonesian Ministry of Finance’s Indonesia Endowment Fund for Education (LPDP) for providing financial support for the publication of this article and for the authors’ pursuit of postgraduate education.Disclosure StatementThe authors reported no potential conflicts of interest.Additional informationFundingThis study was supported by the Lembaga Pengelola Dana Pendidikan.
期刊介绍：
Structural Equation Modeling: A Multidisciplinary Journal publishes refereed scholarly work from all academic disciplines interested in structural equation modeling. These disciplines include, but are not limited to, psychology, medicine, sociology, education, political science, economics, management, and business/marketing. Theoretical articles address new developments; applied articles deal with innovative structural equation modeling applications; the Teacher’s Corner provides instructional modules on aspects of structural equation modeling; book and software reviews examine new modeling information and techniques; and advertising alerts readers to new products. Comments on technical or substantive issues addressed in articles or reviews published in the journal are encouraged; comments are reviewed, and authors of the original works are invited to respond.
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