On Tue, 3 Aug 2004, Peter Alspach wrote: [Lines wrapped for legibility.]
> I'm having a little difficulty getting the correct standard errors from > a glm.object (R 1.9.0 under Windows XP 5.1). predict() will gives > standard errors of the predicted values, but I am wanting the standard > errors of the mean. > > To clarify: > > Assume I have a 4x3x2 factorial with 2 complete replications (i.e. 48 > observations, I've appended a dummy set of data at the end of this > message). Call the treatments trt1 (4 levels), trt2 (3 levels) and trt3 > (2 levels) and the replications rep - all are factors. The observed > data is S. Then: > > temp.aov <- aov(S~rep+trt1*trt2*trt3, data=dummy.data) > model.tables(temp.aov, type='mean', se=T) > > Returns the means, but states "Design is unbalanced - use se.contrasts > for se's" which is a little surprising since the design is balanced. If you used the default treatment contrasts, it is not. Try Helmert contrasts with aov(). > Nevertheless, se.contrast gives what I'd expect: > > se.contrast(temp.aov, list(trt1==0, trt1==1), data=dummy.data) > [1] 5.960012 > > i.e. standard error of mean is 5.960012/sqrt(2) = 4.214, which is the > sqrt(anova(temp.aov)[9,3]/12) as expected. Similarly for interactions, > e.g.: > > se.contrast(temp.aov, list(trt1==0 & trt2==0, trt1==1 & trt2==1), > data=dummy.data)/sqrt(2) > [1] 7.299494 > > How do I get the equivalent of these standard errors if I have used > lm(), and by extension glm()? I think I should be able to get these > using predict(..., type='terms', se=T) or coef(summary()) but can't > quite see how. In either case you can predict something you want to estimate and use predict(, se=TRUE). -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
