This sounds interesting, thank you. I'll have a look. jason
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.lampria...@manchester.ac.uk --- On Wed, 8/9/10, Greg Snow <greg.s...@imail.org> wrote: > From: Greg Snow <greg.s...@imail.org> > Subject: RE: [R] two questions > To: "Iasonas Lamprianou" <lampria...@yahoo.com>, "juan xiong" > <xiongjuan2...@gmail.com>, "Dennis Murphy" <djmu...@gmail.com> > Cc: "r-help@r-project.org" <r-help@r-project.org> > Date: Wednesday, 8 September, 2010, 17:41 > 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.s...@imail.org > 801.408.8111 > > > > -----Original Message----- > > From: r-help-boun...@r-project.org > [mailto:r-help-boun...@r- > > project.org] On Behalf Of Iasonas Lamprianou > > Sent: Tuesday, September 07, 2010 12:25 AM > > To: juan xiong; Dennis Murphy > > Cc: r-help@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.lampria...@manchester.ac.uk > > > > --- On Tue, 7/9/10, Dennis Murphy <djmu...@gmail.com> > wrote: > > > > From: Dennis Murphy <djmu...@gmail.com> > > Subject: Re: [R] two questions > > To: "juan xiong" <xiongjuan2...@gmail.com> > > Cc: "David Winsemius" <dwinsem...@comcast.net>, > r-help@r-project.org, > > "Iasonas Lamprianou" <lampria...@yahoo.com> > > Date: Tuesday, 7 September, 2010, 4:47 > > > > Hi: > > > > On Mon, Sep 6, 2010 at 5:26 PM, juan xiong <xiongjuan2...@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 > > <dwinsem...@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@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@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@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.
