Article: Haenlein, Michael, and Andreas M. Kaplan. 2004. “A Beginner’s Guide to Partial Least Squares Analysis.” Understanding Statistics 3 (4):283-297. doi: 10.1207/s15328031us0304_4.
Full article: here
PLS-SEM is a powerful statistical method to analyze how several variables, each consisting of a number of indicators, influence eachother. The approach is referred to as a “silver bullet” – a “quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent constructs” (Hair et al. 2004)
Although beeing from 2004, and PLS-SEM has developed since then, this article gives a reasonable and clear description of this statistical tool.
The article compares PLS-SEM to other approaches, especially CB-SEM. CB-SEM is similar, but also quite different, being covariance-based, whereas PLS-SEM is variance-based.
It’s quite easy to use a PLS-SEM analysis tool, like Smart-PLS, but if you havent used second-generation algorithms like PLS-SEM, its a bit like getting into a rocket-ship, after being used to riding a scooter (ok, slightly exaggerated). To know what the results actually mean, you ought to have at least a basic understanding of whats under the hood. This article lets you have a peek.
Of course – if you want to dig in – have a go at this : https://www.amazon.com/Partial-Squares-Structural-Equation-Modeling/dp/148337744X
Study in progress 