You do that through random means of the within-level factor. This assumes that the between-level variation in the indicators is only due to the factor, not item-specific. This then calls for equality of factor loadings across levels:
%within% fw by y1 y2-y10 (2-10); %between% fb by y1 y2-y10 (2-10);
Often, however, the between-level variation is item-specific and the above model doesn't fit.
Edward Mak posted on Thursday, August 14, 2008 - 9:33 pm
Thank you for your quick reply. ButI do not understand the program you wrote. Could you briefly explan it ?
Thank you very much.
Edward Mak posted on Thursday, August 14, 2008 - 9:47 pm
I have three more questions. when i read the user guide, variables such as m, w, etc were used. I know m = mean, and w=within, etc. But is it the default meaning. When we use m, Mplus will think it as mean?
the second question is if m, w, etc were not default, how could i get it?
And the last question is, could you recommend any book to me about how to write Mplus program and how to interpret the results?
Please see the examples in Chapter 9 of the user's guide for an explanation of the language.
Please see page 15 of the user's guide for a description of the conventions we use in the user's guide examples. You understanding is not correct. They are only names. They have no impact on the analysis.
See Confirmatory Factor Analysis for Applied Research by Timothy A. Brown.
Xu, Man posted on Sunday, September 07, 2008 - 4:51 am
But why "... This then calls for equality of factor loadings across levels"?