Hi,

SEM - yes if you treat them as ordered categorical variables and use asymptotically distribution free estimator.

EFA - if using maximum likelihood then no because it is concerned with normality. You can use principal component within EFA and it makes no assumption regarding normality and often used for ordinal and skewed data.

Hi,

SEM - yes if you treat them as ordered categorical variables and use asymptotically distribution free estimator.

EFA - if using maximum likelihood then no because it is concerned with normality. You can use principal component within EFA and it makes no assumption regarding normality and often used for ordinal and skewed data.

Hi Mash Hamid. If PCA, what rotation can be performed for this data set?

If the factors are uncorrelated and not dependent on each other then orthognal. If the factors are correlated then oblique. How to decide between the two rotations is to do both and look at the factor loadings of both rotations. If factors are not correlated then the solution of oblique will turn out orthogonal, the one obtained by varimax. If oblique is different then you have to make a judgement. It depends on your dataset. In social science and psychology, they are often correlated but in science they are usually not. Hope this helps.

Dear Mr. Hamid, your statement regarding using PCA for skewed ordinal data sounds very interesting. Would you please provide a reference for it as well? Thx a lot!

Dear Mario,

Timothy Brown has devoted an entire topic to EFA in his book "Confirmatory Factor Analysis for Applied Research" and is a good starting point. The thing to remember about EFA and PCA is that EFA assumes normality but PCA does not. PCA is very robust compared to EFA and not affected by normality. Another source is Multivariate Data Analysis by Hair

If one of the dimensions of a variable in the model is the explored then can we skip the EFA to run the model on the SmartPLS 3?

Dear All,

I have a model in which the dependent variable is the innovation and the two other variables (items adapted). the factors or the dimension are three. The two dimensions have been adapted. However, the items of the third dimensions have been explored. I want to do the data analysis in the SmartPLS 3. 

As I have explored only the one of the three dimensions of the innovation; and I am sure that items of that the dimension do only belong to the innovation construct, therefore I conclude that factor structure is quite clear. Hence, there is no need to do EFA.

Is it correct? Could you provide me the reference to refer in this regard?

Waiting fir the kind response,

Best and the respectful regards, 

If one of the dimensions of a variable in the model is the.... Available from: https://www.researchgate.net/post/If_one_of_the_dimensions_of_a_variable_in_the_model_is_the_explored_then_can_we_skip_the_EFA_to_run_the_model_on_the_SmartPLS_3l [accessed Sep 3, 2017].