The usual least-squares methods are fairly robust to departures from
normality. Furthermore, it is the residuals that are assumed to be
normally distributed (not the marginal distributions that you are
probably looking at) , so it does not sound as though you have yet
examined the data properly. Tell us what the descriptive stats (say
the means, variance, 10th and 90th percentiles) are on the residuals
within cells cross-classified by the gender and city-of-birth
variables (say the means, variance, 10th and 90th percentiles).
On Sep 6, 2010, at 4:34 PM, Iasonas Lamprianou wrote:
>
> Dear friends, two questions
>
> (1) does anyone know if there are any non-parametric equivalents of
> the two-way ANOVA in R? I have an ordinal non-normally distributed
> dependent variable and two factors (gender and city of birth).
> Normally, one would try a two-way anova, but if R has any non-
> parametric equivalents, that might be great.
There is an entire task view page on robust methods if you decide to
press on with this quest.
> (2) Also, if the interaction of gender and city of birth is
> statistically significant, which post-hoc tests should I run?
How many cities are we talking about?
> Thanks
>
> Jason
>
>
> Dr. Iasonas Lamprianou
--
David Winsemius, MD
West Hartford, CT