I think you need to add factors="all" to gen.factorial(), otherwise the
model df will be less than what you expect.
gen.orthogonal.design(c(2,2,3,3,3,3,2,2),numCards=16)
[EMAIL PROTECTED] wrote:
> sorry, some small mistakes in the previuos syntax. This works!
>
> design.test <- gen.orthogonal.design(c(2,4,3),numCards=16)
> design.test
>
> gen.orthogonal.design <- function(listFactors,numCards){
> library(AlgDesign)
> FactorsNames<-c("A","B","C","D","E","F","G","H","J","K","L")
> numFactors<-length(listFactors)
>
> dat<-gen.factorial(listFactors,center=FALSE,varNames=FactorsNames[1:numFacto
> rs])
>
> desPB<-optFederov(~.,dat,nRepeats=20,approximate=FALSE,nTrials=numCards)
> design<-desPB$design#[,2:(numFactors+1)]
> cat("Number of trials: ", fill=T, length(design[,1]), append=T)
> print(cor(design))
> return(design)
> }
>
> However, it is necessary to run the function and guess numCards until the
> correlation matrix is diagonal and all levels are selected for the final
> design.
> Any idea how to solve this problem without an iterative function?
>
> Roberto Furlan
> University of Turin, Italy
>
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Bob Wheeler --- http://www.bobwheeler.com/
ECHIP, Inc. --- Randomness comes in bunches.
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