R help - Nov 2005 - model.matrix for non-hierarchical models

Dear R-users,

Using the function model.matrix I noticed the following
behaviour (example below): Using the formula "~ a + a:b" will
give a matrix of the same dimension as using "~ a * b". In the
first case there are additional columns for the interaction (to
compensate for the missing main-effect).

dd <- data.frame(a = gl(3,4), b = gl(4,1,12))
model.matrix(~ a*b, dd, contrasts = list(a="contr.sum", 
             b="contr.sum"))
model.matrix(~ a + a:b, dd, contrasts = list(a="contr.sum", 
             b="contr.sum"))

Is there any way to get the design matrix corresponding to "~ a
+ a:b" or do I have to do this manually?

Thanks for your help,

Lukas Meier

Lukas Meier <meier at stat.math.ethz.ch> writes:
> Dear R-users,
> 
> Using the function model.matrix I noticed the following
> behaviour (example below): Using the formula "~ a + a:b" will
> give a matrix of the same dimension as using "~ a * b". In the
> first case there are additional columns for the interaction (to
> compensate for the missing main-effect).
> 
> dd <- data.frame(a = gl(3,4), b = gl(4,1,12))
> model.matrix(~ a*b, dd, contrasts = list(a="contr.sum", 
>              b="contr.sum"))
> model.matrix(~ a + a:b, dd, contrasts = list(a="contr.sum", 
>              b="contr.sum"))
> 
> Is there any way to get the design matrix corresponding to "~ a
> + a:b" or do I have to do this manually?
The design matrix corresponding to ~ a + a:b is what you go above. If
that wasn't what you wanted, perhaps you should tell us what you did
want.
 

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