I am trying to fit a normal linear model with response y and predictor x and two factors sex and group.
I would like each combination of sex and group to have individual slopes and then subsequently have parallel slopes.
I tried the model y ~ x*sex*group and it seemed to work for the first case..  Is this how it is supposed to be done?  For the second the model y ~ sex + group seems to work.
 
In a similar vein I wish to fit a logistic model to a binary response "last" is terms of two predictors, education and age, and factors "region", "ccm", "ever", and "diss".  First allowing education and age to have different slopes at all factor levels.  Secondly, to have parallel slopes at all factor levels.  We wish to compare the models using AIC, BIC etc.  How do I specify these models in R?
 
Help would be most appreciated.  I am a relatively new user.
 
John
 
Prof John Fresen (PhD)
Department of Mathematics and Statistics
Medical University of Southern Africa
PO Box 107
MEDUNSA
0204
South Africa
e-mail: jfresen@medunsa.ac.za
tel: +27 12 521 4420
 

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