I have 12 manifest variables, none of which is normally distributed. As far as I know this makes my data unsuitable for a CFA with maximum likelihood estimation (?). I am not sure, however, which alternative estimation method should be used instead. Apart from practical advice I am also thankful if you could point me to any papers discussing this.

Thanks in advance!

(I am not sure that it helps much in this case, but just to give you some background: My data is from a mood measure. Based on theory as well as on a previous EFA that was not done on the same sample I expect four latent factors, with three of the manifest variables loading on each factor.)