[R] indicator or deviation contrasts in log-linear modelling

[maiya]

I realise that in the case of loglin the parameters are clacluated post
festum from the cell frequencies,
however other programmes that use Newton-Raphson as opposed to IPF work the
other way round, right?
In which case one would expect the output of parameters to be limited to the
particular contrast used. But since loglin uses IPF I would have thought the
choice of style of parameter to be output could be made...
Anyway, this is the line that interests me:

> 	lm( as.vector( loglin(...,fit=TRUE)$fit ) ~ < your favored contrasts > )

only I'm not profficient in R to figure out the last term :(
How would I go about this then if my prefered contrasti is setting the first
categories as reference cats?

I literaly just need the equivalent of

loglin(matrix(c(1,2,3,4), nrow=2), list(c(1,2)), param=TRUE)

which would give me parameters under indicator contrast. glm... well, I'd
have to work on it

Regarding the more general points 

ad 2) I would have thought that direct inspection of cell frequencies is
precisely the wrong/misleading thing to do - the highest order coefficients
can be inspected directly in order to see the interaction without the
(lower) marginal effects, or alternatively the table can be standardized to
uniform margins for the same sort of inspection.

ad 3) and yes, I figured as much! I can't see how lower order terms can be
interpreted at all if higher order interactions exist? I've seen it done,
e.g I've seen it claimed that in a standardized table the lower order terms
are all equal to zero, which is of course not true?

Thanks!
Maja



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