Partial least squares path analysis

February 9, 2013

(This article was first published on Statistical Modeling, Causal Inference, and Social Science » R, and kindly contributed to R-bloggers)

Wayne Folta writes:

I [Folta] was looking for R packages to address a project I’m working on and stumbled onto a package called ‘plspm’. It seems to be a nice package, but the thing I wanted to pass on is the PDF that Gaston Sanchez, its author, wrote that describes PLS Path Analysis in general and shows how to use plspm in particular. It’s like a 200-page R vignette that’s really informative and fun to read. I’d recommend it to you and your readers: even if you don’t want to delve into PLS and plspm deeply, the first seven pages and the Appendix A provide a great read about a grad student, PLS Path Analysis, and the history of the field.

It’s written at a more popular level than you might like. For example, he says at one point: “A moderating effect is the fancy term that some authors use to say that there is a nosy variable M influencing the effect between an independent variable X and a dependent variable Y.” You would obviously never write anything like that [yup — AG], and most of your blog readers are pretty sophisticated.

It appears to me the PLS Path Analysis is an interesting alternative to SEM, based on partial-least-squares rather then ML. Same diagrams, similar results, similar procedures, different underlying mechanism/philosophy. And Gaston gives an interesting history of things and obviously put a lot of work into a 200+ page document and R package.

I don’t know anything about PLS path analysis but I thought I’d pass this on for the benefit of those of you who use these methods.

The post Partial least squares path analysis appeared first on Statistical Modeling, Causal Inference, and Social Science.

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