[R] two questions

[Greg Snow]

Have you considered doing a permutation test on the interaction?

Here is an article that gives the general procedure for a couple of algorithms and a comparison of how well they do:

Anderson, Marti J and Legendre, Pierre; An Empirical Comparison of Permutation Methods for Tests of Partial Regression Coefficients in a Linear Model.  J. Statist. Comput. Simul., 1999, vol 62, pp. 271-303.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Iasonas Lamprianou
> Sent: Tuesday, September 07, 2010 12:25 AM
> To: juan xiong; Dennis Murphy
> Cc: r-help at r-project.org
> Subject: Re: [R] two questions
> 
> By the way, ordinal regression would require huge datasets because my
> dependent variable has around 20 different responses... but again, one
> might say that with so many  ordinal responses, it is as if we have a
> linear/interval variable, right? I just hoped that there would be a
> two-way kruskal-wallis or something like that. On the other hand, what
> is going to happen if I (1) bootstrap data from all cells of my design
> and average the rank ordering of the data of every cell? And then (2)
> do the same but using data from a uniform/normal distribution so that I
> assume that there is no difference between the cells? From point (1) I
> will find the statistical value and from point (2) the expectation and
> then with a third step (3) I can run a chi-square on the
> observed/expected values. Would this be reasonable? But again, how can
> I distinguish between main and interaction effects?
> 
> Dr. Iasonas Lamprianou
> 
> 
> 
> 
> 
> Assistant Professor (Educational Research and Evaluation)
> 
> Department of Education Sciences
> 
> European University-Cyprus
> 
> P.O. Box 22006
> 
> 1516 Nicosia
> 
> Cyprus
> 
> Tel.: +357-22-713178
> 
> Fax: +357-22-590539
> 
> 
> 
> 
> 
> Honorary Research Fellow
> 
> Department of Education
> 
> The University of Manchester
> 
> Oxford Road, Manchester M13 9PL, UK
> 
> Tel. 0044  161 275 3485
> 
> iasonas.lamprianou at manchester.ac.uk
> 
> --- On Tue, 7/9/10, Dennis Murphy <djmuser at gmail.com> wrote:
> 
> From: Dennis Murphy <djmuser at gmail.com>
> Subject: Re: [R] two questions
> To: "juan xiong" <xiongjuan2000 at gmail.com>
> Cc: "David Winsemius" <dwinsemius at comcast.net>, r-help at r-project.org,
> "Iasonas Lamprianou" <lamprianou at yahoo.com>
> Date: Tuesday, 7 September, 2010, 4:47
> 
> Hi:
> 
> On Mon, Sep 6, 2010 at 5:26 PM, juan xiong <xiongjuan2000 at gmail.com>
> wrote:
> 
> Maybe Friedman test
> 
> The Friedman test corresponds to randomized complete block designs, not
> general two-way classifications. David's advice is sound, but also
> investigate proportional odds models (e.g., lrm in Prof. Harrell's rms
> package) in case the 'usual' approach comes up short. It would be
> helpful to know the number of response categories and some idea of the
> number of cities-of-birth under study, though...
> 
> 
> HTH,
> Dennis
> 
> 
> 
> 
> On Mon, Sep 6, 2010 at 4:47 PM, David Winsemius
> <dwinsemius at comcast.net>wrote:
> 
> 
> 
> > 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
> 
> >
> 
> >
> 
> > ______________________________________________
> 
> > R-help at r-project.org mailing list
> 
> > https://stat.ethz.ch/mailman/listinfo/r-help
> 
> > PLEASE do read the posting guide
> 
> > http://www.R-project.org/posting-guide.html
> 
> > and provide commented, minimal, self-contained, reproducible code.
> 
> >
> 
> 
> 
>         [[alternative HTML version deleted]]
> 
> 
> 
> ______________________________________________
> 
> R-help at r-project.org mailing list
> 
> https://stat.ethz.ch/mailman/listinfo/r-help
> 
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> 
> and provide commented, minimal, self-contained, reproducible code.
> 
> 
> 
> 
> 
> 
> 
> 	[[alternative HTML version deleted]]