library(psych) x <- as.data.frame(read.table(file='https://automated.biganalytics.eu/download/utaut.csv',sep=',',header=T)) x$U25 <- 6-x$U25 if(par2 == 'female') x <- x[x$Gender==0,] if(par2 == 'male') x <- x[x$Gender==1,] if(par3 == 'prep') x <- x[x$Pop==1,] if(par3 == 'bachelor') x <- x[x$Pop==0,] if(par4 != 'all') { x <- x[x$Year==as.numeric(par4),] } cAc <- with(x,cbind( A1, A2, A3, A4, A5, A6, A7, A8, A9,A10)) cAs <- with(x,cbind(A11,A12,A13,A14,A15,A16,A17,A18,A19,A20)) cA <- cbind(cAc,cAs) cCa <- with(x,cbind(C1,C3,C5,C7, C9,C11,C13,C15,C17,C19,C21,C23,C25,C27,C29,C31,C33,C35,C37,C39,C41,C43,C45,C47)) cCp <- with(x,cbind(C2,C4,C6,C8,C10,C12,C14,C16,C18,C20,C22,C24,C26,C28,C30,C32,C34,C36,C38,C40,C42,C44,C46,C48)) cC <- cbind(cCa,cCp) cU <- with(x,cbind(U1,U2,U3,U4,U5,U6,U7,U8,U9,U10,U11,U12,U13,U14,U15,U16,U17,U18,U19,U20,U21,U22,U23,U24,U25,U26,U27,U28,U29,U30,U31,U32,U33)) cE <- with(x,cbind(BC,NNZFG,MRT,AFL,LPM,LPC,W,WPA)) cX <- with(x,cbind(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18)) if (par5=='ATTLES connected') x <- cAc if (par5=='ATTLES separate') x <- cAs if (par5=='ATTLES all') x <- cA if (par5=='COLLES actuals') x <- cCa if (par5=='COLLES preferred') x <- cCp if (par5=='COLLES all') x <- cC if (par5=='CSUQ') x <- cU if (par5=='Learning Activities') x <- cE if (par5=='Exam Items') x <- cX ncol <- length(x[1,]) for (jjj in 1:ncol) { x <- x[!is.na(x[,jjj]),] } par1 <- as.numeric(par1) nrows <- length(x[,1]) rownames(x) <- 1:nrows y <- x fit <- principal(y, nfactors=par1, rotate='varimax') fit fs <- factor.scores(y,fit) fs bitmap(file='test1.png') fa.diagram(fit) dev.off() bitmap(file='test2.png') plot(fs,pch=20) text(fs,labels=rownames(y),pos=3) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Rotated Factor Loadings',par1+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variables',1,TRUE) for (i in 1:par1) { a<-table.element(a,paste('Factor',i,sep=''),1,TRUE) } a<-table.row.end(a) for (j in 1:length(fit$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')
|