search for: designmatrix

...dition, Region), idesign=~Condition*Region ) ) I'm now trying to do post-hoc comparisons between all levels of Condition using glht() from the multcomp package. I do this using the way that has worked for me with lmer() objects in the past: set up a contrast matrix and then feed it to glht(): designmatrix <- matrix(0, nrow=3, ncol=18) rownames(designmatrix) <- c("Cond1_minus_Cond2", "Cond3_minus_Cond1", "Cond3_minus_Cond2") designmatrix[1, 1:6] <- 1 designmatrix[1, 7:12] <- -1 designmatrix[2, 1:6] <- -1 designmatrix[2, 13:18] <- 1 designmatrix[3, 13:18...

...y(nlme) data(Orthodont) #108 dental measurements on 27 subjects # m1<-lme(distance~age,random=~1|Subject,data=Orthodont) # summary(m1) # ... # Random effects: # Formula: ~1 | Subject # (Intercept) Residual # StdDev: 2.114724 1.431592 -> lambda.REML=2.114^2/1.431^2 = 2.182382 #DesignMatrix for fixed Effects X<-cbind(rep(1,108),Orthodont$age) #DesignMatrix of RandomEffects Z<-matrix(data=c(rep(1,4),rep(0,108)),nrow=108,ncol=27) #Corr(RanEf)^0.5 = 27 x 27 Identity, since RandomIntercepts are independent sqrt.Sigma<-diag(27) K<-27 #number of subjects/ random intercepts...

Hello R-users, First my settings: R-1.8.1, compiled as a 64bit application for a Solaris 5.8, 64 bit. The OS has 8Gb of RAM available and I am the sole user of the machine, hence pretty much all the 8Gb are available to R. I am pretty new to R and I am having a hard time to work with large data sets, which make up over 90% of the anlyses done here. The data set I imported in R, from S+, has a