I should have mentioned that I am using the lmer library for my analyses, just in case other methods provide results differently.
Daniel ------------------------- cuncta stricte discussurus ------------------------- -----Ursprüngliche Nachricht----- Von: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Im Auftrag von Daniel Malter Gesendet: Saturday, July 25, 2009 9:25 PM An: 'R help' Betreff: [R] Assessing standard errors of polynomial contrasts Hi, using polynomial contrasts for the ordered factors in an experiment leads to much nicer covariance structure than using treatment contrasts. It is easy to assess the mean effect for each of the experimental groups. However, standard errors are provided only for the components of the orthogonal contrasts. I wonder how to assess the standard errors not of the components, but of the respective experimental treatment groups as a whole. If the correlation between the fixed effects is small, can the standard error be approximated by sqrt( sum (SE of components^2))) ? I know this is a stats rather than an R question, but I thought one of the many specialists in experiments might be able to help me out quickly on this or point me to appropriate literature. Thanks, Daniel ----------------------------------------------- "Who has visions should see a doctor," Helmut Schmidt, German Chancellor (1974-1982). ______________________________________________ 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.
