#### Read in data

chemdata <- read.table("C:\\t24.1")
chemdatanomiss <- na.omit(chemdata)
names(chemdatanomiss) <- c("Tab","Set","Lab1","Lab2",
                           "O1","G1", 
                           "O2","G2", 
                           "O3","G3", 
                           "O4","G4", 
                           "O5","G5",
                           "O6","G6",
                           "O7","G7",
                           "O8","G8",
                           "O9","G9",
                           "O10","G10")

### Need to reorganize data for analaysis. Put into a LONG vector
### See what dimensions we are dealing with
dim(chemdatanomiss)
### 141 x 24

newdatamat <- matrix(rep(0, 141 *10 * 4),ncol=4)

for( i in 1: 141){
	for( j in 1:10){
# Read off the yij		
		newdatamat[(i-1) * 10 + j,1] <- chemdatanomiss[i,5 + (j-1) * 2]
# Read off lab
             newdatamat[(i-1) * 10 + j,2] <- chemdatanomiss[i,3]
# Read off batch
             newdatamat[(i-1) * 10 + j,3] <- j
# Read off method  
		newdatamat[(i-1) * 10 + j,4] <- chemdatanomiss[i,6 + (j-1) * 2]
	}
print(paste("Iteration ", i))
}

dimnames(newdatamat) <- list(NULL,c("Value","Lab","Batch","Method"))
boxplot(split(newdatamat[,1],newdatamat[,4]),varwidth=T)

as.factor(newdatamat[,2])
as.factor(newdatamat[,3])
as.factor(newdatamat[,4])

is.random(newdatamat[,2]) <- T

is.random(newdatamat[,2])


varcomp(newdatamat[,1] ~ newdatamat[,2] + newdatamat[,3] + newdatamat[,4])



varcomp(newdatamat[,1] ~