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Data X:
x <- array(list('Environmental legislation' 4 4 5 5 5 4 4 4 4 5 5 4 1 4 4 4 4 5 4 3 5 4 3 5 4 5 5 5 4 3 4 3 2 4 5 3 4 2 4 4 4 5 4 4 4 1 'Planning policies' 3 5 4 5 5 4 3 5 4 5 5 4 1 4 4 4 4 2 4 4 4 4 4 4 3 4 5 5 4 2 3 4 5 3 4 4 5 4 4 4 4 5 4 4 4 4 'Corporate Social Responsibilities' 5 5 2 5 2 3 4 4 5 3 4 5 1 4 4 4 4 3 5 3 4 3 2 4 3 3 4 5 5 4 5 1 5 5 4 5 1 4 2 3 4 2 4 4 4 3 'Partnership with local councils' 4 4 3 2 2 3 3 2 3 3 4 4 1 4 4 4 4 2 5 3 4 3 3 3 3 4 3 3 2 5 5 5 4 1 4 5 5 2 1 5 2 4 5 5 5 5 'Business risk of future legislation' 4 3 3 3 2 3 4 2 3 3 4 4 2 4 4 4 4 1 5 4 4 4 3 3 3 3 3 5 5 4 5 4 5 4 5 5 4 5 4 2 4 4 4 4 1 1 'Marketing benefits' 3 1 2 3 2 4 4 2 3 2 4 4 2 4 4 4 3 1 5 3 4 3 4 3 3 2 4 5 4 4 5 1 4 5 4 2 5 4 1 5 4 5 4 5 5 4 'Customer demand' 3 2 1 3 5 3 3 2 4 2 4 4 2 4 4 4 3 3 4 5 4 4 4 3 3 4 4 5 4 4 5 4 5 4 4 5 4 5 4 5 5 4 5 5 5 4 'Eco-town opportunities' 3 3 4 3 5 3 5 2 4 2 4 4 2 4 3 4 3 2 4 3 4 3 4 4 3 4 4 5 5 4 3 4 5 5 3 5 4 5 5 4 4 4 4 5 5 5 'Potential sales price premiums' 3 2 3 3 1 4 4 2 4 2 4 4 2 4 5 4 3 4 5 3 3 2 4 4 2 2 4 5 4 4 5 1 4 5 3 4 5 4 5 3 4 4 5 5 4 5 'Fiscal incentives (i.e. Tax reliefs. subsidy)' 5 4 3 4 1 4 3 2 5 5 4 5 2 4 5 4 4 5 4 5 4 5 5 4 2 4 5 5 4 3 5 3 4 5 1 4 5 5 2 3 4 5 4 5 4 4 'Government grants (i.e. Extra funding)' 4 4 3 4 1 5 4 5 5 5 4 5 2 4 5 4 4 4 4 5 4 5 5 3 2 4 5 5 4 4 5 5 1 4 2 5 4 4 5 5 4 5 5 5 5 5
Names of X columns:
label 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
Number of Factors
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R Code
par1 <- '2' library(psych) par1 <- as.numeric(par1) x <- t(x) nrows <- length(x[,1]) ncols <- length(x[1,]) y <- array(as.double(x[1:nrows,2:ncols]),dim=c(nrows,ncols-1)) colnames(y) <- colnames(x)[2:ncols] rownames(y) <- x[,1] y fit <- principal(y, nfactors=par1, rotate='varimax') fit fs <- factor.scores(y,fit) fs bitmap(file='test1.png') fa.diagram(fit) dev.off() bitmap(file='test2.png') plot(fs$scores,pch=20) text(fs$scores,labels=rownames(y),pos=3) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Rotated Factor Loadings',par1+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variables',1,TRUE) for (i in 1:par1) { a<-table.element(a,paste('Factor',i,sep=''),1,TRUE) } a<-table.row.end(a) for (j in 1:length(fit$loadings[,1])) { a<-table.row.start(a) a<-table.element(a,rownames(fit$loadings)[j],header=TRUE) for (i in 1:par1) { a<-table.element(a,round(fit$loadings[j,i],3)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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