The formula should be (diag(n) - 1/n)[, -n] On Sun, Oct 12, 2008 at 1:36 PM, Gabor Grothendieck <[EMAIL PROTECTED]> wrote: > Looks like the contrast matrix for indicator is contr.SAS(n), > for deviation is contr.sum(n) and for simple is: > > (diag(n) - 1/n)[, -1] > > That works at least for the n = 3 example in the link. > Perhaps the others could be checked against SPSS > for a variety of values of n to be sure. > > On Sun, Oct 12, 2008 at 12:32 PM, Chuck Cleland <[EMAIL PROTECTED]> wrote: >> On 10/11/2008 3:31 PM, Ted Harding wrote: >>> Hi Folks, >>> >>> I'm comparing some output from R with output from SPSS. >>> The coefficients of the independent variables (which are >>> all factors, each at 2 levels) are identical. >>> >>> However, R's Intercept (using default contr.treatment) >>> differs from SPSS's 'constant'. It seems that the contrasts >>> were set in SPSS using >>> >>> /CONTRAST (varname)=Simple(1) >>> >>> I can get R's Intercept to match SPSS's 'constant' if I use >>> contr.sum in R. >>> >>> Can someone please confirm that that is a correct match for >>> the SPSS "Simple(1)", with identical effect? >>> >>> And is there a convenient on-line reference where I can look >>> up what SPSS's "/CONTRAST" statements exactly mean? >>> I've done a lot of googling, withbout coming up with anything >>> satisfactory. >>> >>> With thanks, >>> Ted. >> >> Hi Ted: >> Here are two links with the same content giving a brief description of >> SPSS simple contrasts: >> >> http://www.ats.ucla.edu/stat/spss/library/contrast.htm >> http://support.spss.com/productsext/spss/documentation/statistics/articles/contrast.htm >> >> These pages explain how simple contrasts differ from indicator >> (contr.treatment) and deviation (contr.sum) contrasts. For a factor >> with 3 levels, I believe you can reproduce SPSS simple contrasts (with >> the first category as reference) like this: >> >>> C(warpbreaks$tension, contr=matrix(c(-1/3,2/3,-1/3,-1/3,-1/3,2/3), >> ncol=2)) >> ... >> attr(,"contrasts") >> [,1] [,2] >> L -0.3333333 -0.3333333 >> M 0.6666667 -0.3333333 >> H -0.3333333 0.6666667 >> Levels: L M H >> >> For a factor with 2 levels, like this: >> >>> C(warpbreaks$wool, contr=matrix(c(-1/2,1/2), ncol=1)) >> ... >> attr(,"contrasts") >> [,1] >> A -0.5 >> B 0.5 >> Levels: A B >> >> Your description of the effect of SPSS simple contrasts - intercept >> coefficient of contr.sum and non-intercept coefficients of >> contr.treatment - sounds accurate to me. >> >> hope this helps, >> >> Chuck >> >>> -------------------------------------------------------------------- >>> E-Mail: (Ted Harding) <[EMAIL PROTECTED]> >>> Fax-to-email: +44 (0)870 094 0861 >>> Date: 11-Oct-08 Time: 20:31:53 >>> ------------------------------ XFMail ------------------------------ >>> >>> ______________________________________________ >>> 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. >> >> -- >> Chuck Cleland, Ph.D. >> NDRI, Inc. (www.ndri.org) >> 71 West 23rd Street, 8th floor >> New York, NY 10010 >> tel: (212) 845-4495 (Tu, Th) >> tel: (732) 512-0171 (M, W, F) >> fax: (917) 438-0894 >> >> ______________________________________________ >> 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. >> >
______________________________________________ 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.
