Hi all, I am struggling with a strange issue in R that I have not encountered before and I am not sure how to resolve this.
The model looks like this, with all irrelevant variables left out: LABOUR - a dummy variable NONLABOUR = 1 - LABOUR AGE - a categorical variable / factor VOTE - a dummy variable glm(VOTE ~ 0 + LABOUR + NONLABOUR + LABOUR : AGE + NONLABOUR : AGE, family=binomial(link="logit")) In other words, a standard interaction model, but I want to know the intercepts and coefficients for each of the two cases (LABOUR and NONLABOUR), instead of getting coefficients for the differences as in a normal interaction model. But the strange thing is, for the two occurances of the AGE variable, it makes a different choice as to which AGE category to leave out of the regression. The cross-table of AGE with LABOUR does not have empty cells. Anyone any idea what might be going wrong? Or what I could do about this? Thanks in advance for any help! Regards, Jos -- Johan A. Elkink Lecturer School of Politics and International Relations & CHS Graduate School University College Dublin Ph. +353 1 716 7026 | Library Building, Rm 512 http://jaeweb.cantr.net ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.