Hi,
so i have a reflective-formative type models (as seen on the picture attached) and use the repeated indicator approach, and what i did on assessing the model based on what i understand was:
1. calculate the PLS algorithm and see the cronbach alpha, composite reliability and AVE criteria.
2. Since few of my variables on the LOC has low value of AVE composite reliability and cronbachs alpha, i had to eliminate some of the indicators so that i can meets the criteria. Ive read on some journals that if you eliminate an indicator from the LOC, u also have to remove the one in the HOC and vice versa.
The problem is, after i eliminate some of the indiators all of my LOC has already meet the AVE minimum value, but somehow my HOC still has a very low AVE value (0.284, as seen on the second pic attached).
So my question is do i have to keep eliminating the indicators until my HOC's AVE value acceptable (but then id lost quite a lot of indicators on LOC too)? Or am i doing it wrong? Is there any specific guides on this cause im kinda lost right now
Thank you
In addition to the one above, you can try this:
Becker, J.-M., Klein, K. and Wetzels, M. (2012), “Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models”, Long Range Planning, Vol. 45 Nos 5/6, pp. 359-394.
Article Hierarchical Latent Variable Models in PLS-SEM: Guidelines f...
Yes sure, see the guidelines proposed by Van Riel et al. (2017):
https://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2016-0286/full/html
In addition to the one above, you can try this:
Becker, J.-M., Klein, K. and Wetzels, M. (2012), “Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models”, Long Range Planning, Vol. 45 Nos 5/6, pp. 359-394.
Article Hierarchical Latent Variable Models in PLS-SEM: Guidelines f...
I can see your model is a reflective one. And for some of your factors (for the DV), there are only 02 items and for some of your factors (IVs), the items are only 03.
Usually from my experiences, I can tell that deleting the items with lower factor loading is not always the answer, however, for sure any item with factor loading lower than 0.5 must go. Although it is good news that smartPLS can still work with only one ITEM but as per other studies every factor must have at least 03 items for better measurement of the factor.
I believe that if you are having low AVE and Alpha value which is stating that our items and factors have big reliability issues. Your model is showing that you have reliability issues, hence, if I were you I'd rather not delete the low load factor items - I'd go back to the literature and try to figure out if my measurement too and selection of items are Ok or not.
I'd reinstate and check all the items and check the reliability in SPSS also run an exploratory factor analysis to make sure all my items underneath each factor are clustered accordingly with high alpha value and factor loading representing the particular factor. Also not to mention PLS works with small sample size, but still, there is a calculation as per that I believe your simple frame should be containing at least 70 or more respondents, also you can check with G*power software which is more accurate. Sometimes the sample size matters too.
However, with such small info, I am only can help you with the above understanding of mine. So, I will highly recommend you to read the below article of Dr Hair, which is like a bible when it comes to smartPLS guidelines. I strongly believe you will get many answers for the below article.
Thank you.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review.
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