PLS and PLSc for reflective model

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osohaib
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PLS and PLSc for reflective model

Post by osohaib » Sat Nov 25, 2017 9:42 am

I read that we should choose PLSc when the model is all reflective constructs. In my model, all factors are modeled as reflective. I run the PLS and the bootstrap for my model and all the values are good (loadings and p values significant); but when I run PLSc and PLSc bootstrap for the same model, most of the loadings less than 0.70 and p values also very high, which means most of insignificant. Also most AVE values below 0.50. But, the PLS results is all good. Does this mean we should not use SmartPLS for reflective models? Is there any paper or example that show the comparison of PLS and PLSc results for the same reflective model in SmartPLS?

My model with PLS results is attached. Should I continue with PLS results for my reflective model and not to use PLSc, because PLSc results are insignificant? Or how to improve PLSc results?
Last edited by osohaib on Thu Nov 30, 2017 3:14 am, edited 1 time in total.

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cringle
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Re: PLS and PLSc for reflective model

Post by cringle » Sat Nov 25, 2017 10:57 am

If you use composite models, you may just want to use PLS; also PLSc can be used to estimate a model that uses both common factor models and composite models. For the decision, which proxy you would use for a latent variable (composite or common factor), you may find this article useful:
http://www.sciencedirect.com/science/ar ... 6316304404

If you like to estimate factor models, use CB-SEM. Here you need a good fit of the model (https://www.smartpls.com/documentation/ ... /model-fit). However, you can mimic common factor models (and CB-SEM) by using PLSc: https://www.smartpls.com/documentation/ ... ith-cb-sem

However, the usual question that arises: Why would you like to mimic factor models when you can use CB-SEM. Also, when using PLSc to mimick factor models, you need to ensure a good fit for your model. Is the SRMR <0.08 after running PLSc? If the fit is not good, PLSc provides the strange results that you obtained (PLSc and its bootstrapping is very vulnerable to constructs with low reliabilities, e.g., Cronbach's alpha below 0.8).

When you consider composites, you can use the usual PLS-SEM algorithm. A good start to addressing this may be to look into composites as proxies of the conceptual variables of interest. Here are some article that you may find useful:
In addition, here you find some argument when to use PLS-SEM:

Richter, N. F., Cepeda Carrión, G., Roldán, J. L., & Ringle, C. M. (2016). European Management Research Using Partial Least Squares Structural Equation Modeling (PLS-SEM): Editorial. European Management Journal, 34(6), 589-597. http://www.sciencedirect.com/science/ar ... 7316300925

And some argument that you don't want to use:

Rigdon, E. E. (2016). Choosing PLS Path Modeling as Analytical Method in European Management Research: A Realist Perspective. European Management Journal, 34(6), 598-605. http://www.sciencedirect.com/science/ar ... 7316300585

Also, when using composites and PLS-SEM, you may want to assess the predictive quality of the model by using the Blindfolding procedure and reporting the resulting Q² values as well as applying the PLSpredict procedure (which is implemented in SmartPLS). Here is some more info about PLSpredict: https://www.smartpls.com/documentation/ ... es/predict

We hope that you find this ideas helpful!

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cringle
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Re: PLS and PLSc for reflective model

Post by cringle » Sat Nov 25, 2017 12:34 pm

I almost forgot to mention this recent open-access article on the CB-SEM and PLS-SEM debate:

Rigdon, E. E., Sarstedt, M., & Ringle, C. M. (2017). On Comparing Results from CB-SEM and PLS-SEM. Five Perspectives and Five Recommendations. Marketing ZFP, 39(3), 4-16. https://rsw.beck.de/docs/librariesprovi ... f?sfvrsn=0

:)

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cringle
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Re: PLS and PLSc for reflective model

Post by cringle » Sat Nov 25, 2017 4:58 pm

Here you also find some argument on when to use composites and PLS-SEM:

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial Least Squares Structural Equation Modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of Market Research. Heidelberg: Springer. https://www.researchgate.net/publicatio ... n_Modeling

osohaib
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Re: PLS and PLSc for reflective model

Post by osohaib » Thu Nov 30, 2017 10:44 am

Thanks Professor.

I don't have a statistical background, so im sorry if I am asking very basic questions. I am loving SmartPLS but first I am learning first basic concepts.
I understand that we can use PLS-SEM for both composite and common factors models and CB-SEM for only common factor model. But I didn't understand the difference between the composite and common factor models? I know the difference between formative and reflective constructs though, but how would I know if my model is composite or common factor model. For example, if my model has all reflective constructs? or reflective-formative both?

Also, if you could clarify the term "proxy" used in the context.

Many thanx.

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cringle
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Re: PLS and PLSc for reflective model

Post by cringle » Sun Dec 03, 2017 9:48 am

Thanks. You may want to get started with this article (especially the last figure):

Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016). Estimation Issues with PLS and CBSEM: Where the Bias Lies! Journal of Business Research, 69(10), 3998-4010. http://www.sciencedirect.com/science/ar ... 6316304404

And then also take a look at the other literature suggestions.

Best
Christian

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