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Hi, My understanding up to now is that you would have to create an LV for every control measured by just one indicator. This, however, renders new problems: First, constructs shouldn't be measured by just one item and second, this could blow up your required sample size when applying Chin's rule. F...

There is negative numbers beetween, and that should not be possible. Again, the weights are calculated such that latent variables have unit variance and a zero mean. If you unstandardize the weights and apply them to the raw data, you will not have the "issue" of negative latent variable ...

Hello, How would you calc. the score for the LV in the esci model, when you have got the output from smartpls? Under "Calculation Results" you will find a field called "Latent Variable Scores" that will list the latent variable scores for each observation. You can simply highlig...

There is 5 image questions there overall will make the Image index. But there is only 2 qustions to make the Quality index. If you do not use relative weights the score for Image will allways be allot higher than the score for Quality simply because there is 3 more question. In PLS weights are scal...

Hi Kenneth, In PLS latent variables are the weighted sum of their indicators. This is always the case, regardless of whether the latent variables are specified as having formative or reflective indicators. So to compute latent variable scores you simply sum the product of each indicator and it's wei...

Simon, With inner directed indicators you also at least as many observations as indicators, as their weights are determined with a multiple regression. This isn't usually a problem, but as a rule of thumb you should have 10 times as many observations as the structural equation or inner directed late...

Simon, With inner directed indicators you also at least as many observations as indicators, as their weights are determined with a multiple regression. This isn't usually a problem, but as a rule of thumb you should have 10 times as many observations as the structural equation or inner directed late...

Hi Chris,

Just set up "Size of Company" as a latent variable with a single indicator; the two will be synonymous.

Jörg, Because PLS is a regression based technique our models can be estimated using covariance or correlation matrices as input, but that does not mean we do not have exact latent variable scores that are--or could be--calculated. As long as we have the raw data (regardless of whether we use it as i...

I thought about using LISREL or AMOS for the CFA in the first time as well. But the problem with using LISREL for all of my analysis is that 1. I will use formative indicators Conceptually I'm not sure what the point of CFA is if your model is using formative indicators. With formative indicators y...

First, I heard that the interpretation of the PLS Output would be a bit tricky. Are there any main problems about interpreting the influence from one latent variable to another or about interpreting the weights and loadings of the manifest variables? Or is it as "easy" as in linear regres...

John, how would you determine latent variable scores if not as a linear combination of indicators (whether belonging to the block in question or not)? This is another area where PLS and covariance-based SEM butt heads. True latent variables or constructs don't have scores that we can measure. They ...

By the way, please don't take my comments as implying anything negative about PLS. I am a huge PLS fan but it reflects a different model than does covariance based SEM, regardless of estimation mode or how we graph our models. Ignoring the differences between those PLS and covariance based SEM serve...

In both cases, the correlation is 1. Yes, (AX1 + BX2 + CX3) will have a correlation of 1 with (JX1 +KX2 + LX3) for all values of A, B, C, J, K, and L, so long as the pairs (A,J), (B, K) and (C, L) have the same sign (positive or negative). The two weighted sums will have different values, but those...

It is the weights that are always used in PLS to calculate latent variable scores, never the loadings. Graphic conventions of Mode A vs Mode B are just that—conventions for pictorial representation. In all PLS models the weights are always used to construct the latent variables, all that differs bet...