Dear all, please forgive me if this has been asked many times before, but I couldn't find any other info about it. BTW, is there a FAQ section? My problem is this: In market research we deal with many data that are batteries of questionnaire items but where the items are coded as dichotomous variables (e.g., 1 for "applies", 0 for "doesn't apply"). From time to time I hear that it is possible to treat dichotomous variables as metric variables which would allow me to make use of Pearson correlation coefficients or even run PCA or Factor Analysis on such data. However, I haven't found more detailed information on this. Thus, my question(s): (1) Is it indeed possible to treat dichotomous variables in the same way as metric variables? I know that there are probably special techniques in factor analysis and/or correlation (tetrachoric), but I'd rather like to know if I can use the standard techniques without too much loss of interpretability (so that I can use standard stats packages). (2) Can you point me to any references (books, articles) where this issue is addressed? Any comments/input would be truly appreciated. Thanks in advance, Stefan Ahrens IVE Research International, Hamburg, Germany Sent via Deja.com http://www.deja.com/ Before you buy. ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
