A Note on How to Conduct a Factor-Based PLS-SEM Analysis

被引:49
|
作者
Kock, Ned [1 ]
机构
[1] Texas A&M Int Univ, Div Int Business & Technol Studies, Laredo, TX 78041 USA
关键词
Measurement Error; Monte Carlo Simulation; Partial Least Squares; Path Bias; Structural Equation Modeling; Variation Sharing;
D O I
10.4018/ijec.2015070101
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The composite-factor estimation dichotomy has been the epicenter of a long and ongoing debate among proponents and detractors of the use of the partial least squares (PLS) approach for structural equation modeling (SEM). In this brief research note the author discusses the implementation of a new method to conduct factor-based PLS-SEM analyses, which could be a solid step in the resolution of this debate. This method generates estimates of both true composites and factors, in two stages, fully accounting for measurement error. The author's discussion is based on an illustrative model in the field of e-collaboration. A Monte Carlo experiment suggests that model parameters generated by the method are asymptotically unbiased. The method is implemented as part of the software WarpPLS, starting in version 5.0. This note provides enough details for the method's implementation in other venues such as R and GNU Octave.
引用
收藏
页码:1 / 9
页数:9
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