[R] Log-likelihood function

[Prof Brian Ripley]

I think you need to learn about deviances, which R does print.

Log-likelihoods are only defined up to additive constants.  In this case 
the conventional constant differs if you view this as a Poisson or as a 
product-multinomial log-linear model, and R gives you the log-likelihood 
for a Poisson log-linear model (assuming you specified family=poisson). 
However, deviances and differences in log-likelihoods do not depend on 
which.

More details and worked examples can be found in MASS (the book, see the 
FAQ), including other ways to fit log-linear models in R.


On Tue, 1 May 2007, someone ashamed of his real name wrote:

> I've computed a loglinear model on a categorical dataset.  I would like to
> test whether an interaction can be dropped by comparing the log-likelihoods
> from two models(the model with the interaction vs. the model without).
> Since R does not immediately print the log-likelihood when I use the "glm"
> function, I used SAS initially.  After searching for an extracting function,
> I found one in R.  But, the log-likelihood given by SAS is different from
> the one given by R.  I'm not sure if the "logLik" function in R is giving me
> something I don't want.  Or if I'm misinterpreting the SAS output.  Can
> anyone help?
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595