We have a questionnaire, which have many questions on 6-point likert scale. So these variables are ordinal, not normally distributed. In performing factor analysis, there are two major methods in extracting factors, one is maximum likelihood and the other is principle axis factors. The maximum likelihood is said to perform better than PAF, but in our case the item variables are ordinal (1-6 likert scale), will this be okay to use maximum likelihood, or better to use PAF?
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A description of different [factor extraction](http://stats.stackexchange.com/q/50745/3277) methods. All of them are linear FA that [is for interval scale data](http://stats.stackexchange.com/q/43304/3277), and ML method assumes multivariate normality. But we often treat likert-type rating scale as interval. If you need to treat it as ordinal, [here is](http://stats.stackexchange.com/q/215404/3277) a number of alternatives to classic FA. – ttnphns Jun 29 '16 at 22:54