High Negative Outer Weights
Posted: Fri Dec 11, 2015 7:20 pm
Hello fellow SmartPLSler,
from studying this forum and PLS literature for quite a while now, I know that this topic has been addressed already. However, so far I was unable to find a sufficient answer to the following issue:
After running the software, I was exposed to unusual results for my outer weights, especially when running a smaller sample to do a group analysis.
Here are the results (example; bigger samples also lead to a negative or very low value):
sample size 48 (using the thumb rule 50 is advised for a max. of 5 connections)
Outer Weights:
a 0,510
b 0,684
c -0,775
d 0,550
e -0,029
Respective VIF:
a 3,103
b 1,514
c 3,068
d 3,031
e 3,465
From my understanding, since all VIF values are <5, the VIF values indicate no collinearity issues. Is this assumption correct? (1)
My follow up question is, how should I interpret these high negative results? (2)
From what I have read so far, a low value of an outer weight indicates a low contribution to the latent variable. So what does a negative value indicate? (4)
Do I just state that the negative weights do not contribute at all to the construct? (3)
If the VIF is sufficient and does not indicate a collinearity issue (following Hair et al. 2013), I check the significance, and the respective outer loading, if outer weight is not significant. In case, a on outer loading's value is <0.5, I should delete this indicator, right? (5)
Could the issue arise because of the sample size? Would deleting indicator c one way to solve indicator weight problem and potential problem of a too small of a sample?
Thank you, for your help and advise.
from studying this forum and PLS literature for quite a while now, I know that this topic has been addressed already. However, so far I was unable to find a sufficient answer to the following issue:
After running the software, I was exposed to unusual results for my outer weights, especially when running a smaller sample to do a group analysis.
Here are the results (example; bigger samples also lead to a negative or very low value):
sample size 48 (using the thumb rule 50 is advised for a max. of 5 connections)
Outer Weights:
a 0,510
b 0,684
c -0,775
d 0,550
e -0,029
Respective VIF:
a 3,103
b 1,514
c 3,068
d 3,031
e 3,465
From my understanding, since all VIF values are <5, the VIF values indicate no collinearity issues. Is this assumption correct? (1)
My follow up question is, how should I interpret these high negative results? (2)
From what I have read so far, a low value of an outer weight indicates a low contribution to the latent variable. So what does a negative value indicate? (4)
Do I just state that the negative weights do not contribute at all to the construct? (3)
If the VIF is sufficient and does not indicate a collinearity issue (following Hair et al. 2013), I check the significance, and the respective outer loading, if outer weight is not significant. In case, a on outer loading's value is <0.5, I should delete this indicator, right? (5)
Could the issue arise because of the sample size? Would deleting indicator c one way to solve indicator weight problem and potential problem of a too small of a sample?
Thank you, for your help and advise.