On the role of partial least squares in path analysis for the social sciences

被引：20
作者：
Cook, R. Dennis [1 ]
Forzani, Liliana [2 ,3 ]
机构：
[1] Univ Minnesota, Sch Stat, Minneapolis, MN 55455 USA
[2] UNL, Fac Ingn Quim, Santa Fe, Argentina
[3] Consejo Nacl Invest Cient & Tecn, Santa Fe, Argentina
来源：
JOURNAL OF BUSINESS RESEARCH | 2023年 / 167卷
关键词：
Envelopes; Reduced rank regression; Reflective path models; Structural equation modeling; EFFICIENT ESTIMATION; ENVELOPE MODELS; COMMON BELIEFS; PLS; COMPLEX;
D O I：
10.1016/j.jbusres.2023.114132
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
We describe the current and potential future roles for partial least squares (PLS) algorithms in path analyses, guided by recent advances in envelope theory. After reviewing the present debate and establishing a context, we conclude that, depending on specific objectives, PLS methods have considerable promise, but that their full potential, while reachable, is not now being realized. The future developments necessary for achieving their full potential in the social sciences are clear and doable, albeit demanding. A critique of covariance-based structural equation modeling (CB-SEM), as it relates to PLS, is given as well. Technical details are available in the appendix.
引用
收藏
页数：16
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