I'm really having a hard time trying to normalize my data. My study is about green IT product acceptance. There are eight factors, six are 5-point Likert scale (Str.disagree - Str.agree), one is 2-point Yes/No question, and the other one is 3-point scale (Don't know/Maybe/Know). I have 618 returned questionnaires.
I add data into SPSS, compute variables, and round them up. I explored skewness and kurtosis of all factors and found that they're not normally distributed. I tried a Two-Step Transformation to Normality and Box-Cox, but the KS and SW Sig. are still .000. However, Q-Q plot change from loosely distributed to perfectly follows the slope.
My questions are:
- Is it a crucial problem if my data isn't normally distributed?
- Someone said Likert scales are not normal in their nature, is that true?
- Do you know any literature to cite and explain why Likert scale isn't normally distributed?
- Do I need to normalize all variables before I do Structural Equation Modeling?