Hi Sara Hoseingholizade

1. To test normality, I recommend interpreting the skewness and kurtosis coefficients instead of statistical tests. In this case, if there are normality problems, parameter estimations can be made with unweighted least squares in SPSS.

2. Multivariate normality test is sufficient.

3. Depends on the statistic to be used. If normality is an assumption of the statistic to use, yes.

Good luck

Thanks Hakan Koğar , I see.

I just got a question, what is Unweighted Least Square? How can I conduct it in SPSS?

Hi again Sara Hoseingholizade

I have an article about this: https://dergipark.org.tr/tr/pub/epod/issue/27317/287601

You can find so much information on other sources too

Here ise SPSS stages on SPSS: SPSS -> analyse -> factor reduction -> factor -> extraction -> method

Thank you so much for the article Hakan Koğar . Well, I used maximum likelihood as a method, as I see you have described all of them perfectly in the article.

Thank you for your nice words Sara Hoseingholizade

Good luck with you research

Dear Sara ,

A multivariate normal distribution is required when using maximum likelihood as the factor extraction method*.

While using using AMOS multivariate normality is required for CFA and to the best of my knowledge, many researchers are tested normality for each item of all variables in a SEM.

Good luck

Treiblmaier, H., & Filzmoser, P. (2010). Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research. Information & management, 47(4), 197-207.