If we check the data, we see a mistake in the entry.

> tbl.8.3
  mara cig alc count
1  Yes Yes Yes   911
2   No  No  No   538
3  Yes Yes Yes    44
4   No  No  No   456
5  Yes Yes Yes     3
6   No  No  No    43
7  Yes Yes Yes     2
8   No  No  No   279

Try:

table8.3 <- read.table(textConnection("alc cig mar count
Yes Yes Yes 911
Yes Yes No  538
Yes No  Yes 44
Yes No  No  456
No  Yes Yes 3
No  Yes No  43
No  No  Yes 2
No  No  No  279"),header=TRUE)
closeAllConnections()
myglm <- glm(count ~ mar+cig+alc, family=poisson, data=table8.3)
myglm$fitted.values

> myglm$fitted.values
        1         2         3         4         5         6
7         8
539.98258 740.22612 282.09123 386.70007  90.59739 124.19392  47.32880
64.87990

This reproduces the fitted values for your example (Agresti, pg 323)

On Wed, Jan 14, 2009 at 7:23 AM, Gerard M. Keogh <GMKeogh@justice.ie> wrote:

>
> Dear all,
>
> sorry to bother you all with this but I've been trying to use the loglm in
> MASS package (v2.8.0) and cannot get any sensible output.
> I'm wondering am I doing something very foolish or missing something
> obvious.
>
> For example, I tried the documentation help(loglm) example - here's the
> code
>
>         # Case 1: frequencies specified as an array.
>         sapply(minn38, function(x) length(levels(x)))
>         ## hs phs fol sex f
>         ##  3   4   7   2 0
>         minn38a <- array(0, c(3,4,7,2), lapply(minn38[, -5], levels))
>         minn38a[data.matrix(minn38[,-5])] <- minn38$fol
>         fm <- loglm(~1 + 2 + 3 + 4, minn38a)  # numerals as names.
>         deviance(fm)
>         > [1] 0
>
> The deviance is zero.
> I tried other examples as well (Laura Thompson) and get pretty much
> nonsense.
>
> E.g.
>
>      library(MASS)
>      options(contrasts=c("contr.treatment", "contr.poly"))
>      tbl.8.3 = data.frame(mara
>      =factor(c("Yes","No"),levels=c("Yes","No")),
>                            cig
>      =factor(c("Yes","No"),levels=c("No","Yes")),
>                            alc
>      =factor(c("Yes","No"),levels=c("Yes","No")),
>                            count=c(911,538,44,456,3,43,2,279) )
>      fit.acm = loglm( count ~ alc*cig*mara,data=tbl.8.3, param=T, fit=T)
>
>
> Any advice greatly appreciated.
>
> Gerard
>
>
>
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