Hi all I understand by clicking the latent variables tab after running PLS algorithm, they are the factor scores of each construct for the data set.
All my scales are 7point Likert scales from 1 to 7. If the path is positive, by multiplying the factor loadings I would expect positive numbers. However I found something strange. Even for one construct which has only two indicators, all positive loadings, the factor score turns out to have negative. Why is that so? My purpose is very simple, just to show a descriptive statistics of what is the average rating on that construct.
If my model is A and B > C, while C itself has 3items, what would the latent variable score of C in Smartpls mean then? A combination of the impact of A and B path weights and C indicators, or just C indicators?
Thanks.
Rebecca
Factor Score

 PLS Junior User
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 Joined: Sat Oct 26, 2019 12:50 am
 Real name and title: Rebecca (research student)

 SmartPLS Developer
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 Real name and title: Dr. JanMichael Becker
Re: Factor Score
All data is routinely standardized in the normal PLS algorithm. Hence, latent variable scores are also standardized. If you want unstandardized LV scores you may use the IPMA, which provides unstandardized LV scores.
Dr. JanMichael Becker, University of Cologne, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de