R help - Nov 2009 - multiple comparisons with non homogeneus variances

This is a mixed question, between theory and practice.
I have a dataset with a continous variable grouped by a 33 levels
factor. After having log-tranformed my original data I can assume the
normality of my data but I have two strong departures from the basic
assumptions for anova and t tests: *unbalanced data* (some groups
contain ten samples, others hundreds) and *non homogenity of
variances* (tested with a kruscal test just for a qualitative
assessment).
Is it possible, and how, to make multiple comparisons when these
conditions are met? In past anaylises I've simply used the
pairwise.t.test function to do multiple t-test, but know I have to
consider the above situation...

Thanks a lot,
giovanni

I've forgot to cite the Games and Howell procedure, which some
literature (eg in "Pairwise Multiple Comparison Procedures: A Review"
[1]) referes as a good one for uneual samples and non homogeneus
variance. Yet I haven't found an implementation for R...

giovanni

[1] http://psycnet.apa.org/journals/bul/96/3/589.pdf

2009/11/30 G. Allegri <giohappy at gmail.com>:
> This is a mixed question, between theory and practice.
> I have a dataset with a continous variable grouped by a 33 levels
> factor. After having log-tranformed my original data I can assume the
> normality of my data but I have two strong departures from the basic
> assumptions for anova and t tests: *unbalanced data* (some groups
> contain ten samples, others hundreds) and *non homogenity of
> variances* (tested with a kruscal test just for a qualitative
> assessment).
> Is it possible, and how, to make multiple comparisons when these
> conditions are met? In past anaylises I've simply used the
> pairwise.t.test function to do multiple t-test, but know I have to
> consider the above situation...
>
> Thanks a lot,
> giovanni
>