Consistent and asymptotically normal PLS estimators for linear structural equations

被引:698
作者
Dijkstra, Theo K. [1 ]
Henseler, Jorg [2 ]
机构
[1] Univ Groningen, NL, Dept Econ & Econometr, NL-9747 AE Groningen, Netherlands
[2] Univ Twente, NL, Dept Design Prod & Management, NL-7500 AE Enschede, Netherlands
关键词
Partial least squares; Structural equation modeling; Consistency; Recursiveness; Goodness-of-fit; PARTIAL LEAST-SQUARES; TEST STATISTICS; MANAGEMENT RESEARCH; MODELS; GUIDELINES; SYSTEMS; SEM;
D O I
10.1016/j.csda.2014.07.008
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While maintaining all the strengths of PLS, the consistent version provides two key improvements. Path coefficients, parameters of simultaneous equations, construct correlations, and indicator loadings are estimated consistently. The global goodness-of-fit of the structural model can also now be assessed, which makes PLS suitable for confirmatory research. A Monte Carlo simulation illustrates the new approach and compares it with covariance-based structural equation modeling. (C) 2014 The Authors Published by Elsevier B.V.
引用
收藏
页码:10 / 23
页数:14
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