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Type 'q()' to quit R. > par5 = 'ATTLES all' > par4 = 'all' > par3 = 'all' > par2 = 'male' > par1 = '2' > par5 <- 'ATTLES all' > par4 <- 'all' > par3 <- 'all' > par2 <- 'male' > par1 <- '2' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: root > #To cite this work: Wessa P., 2012, Factor Analysis for Information Management 2 (v1.0.7) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_factor_analysis.wasp/ > #Source of accompanying publication: > # > library(psych) > x <- as.data.frame(read.table(file='http://www.wessa.net/download/utaut.csv',sep=',',header=T)) > x$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 Principal Components Analysis Call: principal(r = y, nfactors = par1, rotate = "varimax") Standardized loadings based upon correlation matrix RC1 RC2 h2 u2 A1 0.58 -0.02 0.33 0.67 A2 -0.11 0.44 0.21 0.79 A3 0.44 0.28 0.28 0.72 A4 -0.06 0.51 0.26 0.74 A5 0.17 0.46 0.24 0.76 A6 0.42 0.41 0.34 0.66 A7 0.32 0.38 0.25 0.75 A8 0.34 0.53 0.39 0.61 A9 0.18 0.40 0.19 0.81 A10 0.49 0.15 0.26 0.74 A11 0.52 -0.37 0.41 0.59 A12 0.13 0.55 0.32 0.68 A13 -0.11 0.54 0.30 0.70 A14 0.28 0.36 0.21 0.79 A15 0.50 0.20 0.29 0.71 A16 0.59 -0.23 0.40 0.60 A17 0.46 0.11 0.22 0.78 A18 0.39 0.19 0.19 0.81 A19 0.23 0.48 0.28 0.72 A20 0.48 0.09 0.24 0.76 RC1 RC2 SS loadings 2.87 2.74 Proportion Var 0.14 0.14 Cumulative Var 0.14 0.28 Test of the hypothesis that 2 factors are sufficient. The degrees of freedom for the null model are 190 and the objective function was 2.79 The degrees of freedom for the model are 151 and the objective function was 0.86 The number of observations was 543 with Chi Square = 458.38 with prob < 1e-32 Fit based upon off diagonal values = 0.79> fs <- factor.scores(y,fit) > fs RC1 RC2 1 -0.732909432 0.006457367 2 0.533694822 -0.056540562 3 0.810571834 -0.378382049 4 0.509707640 -0.112824965 5 1.019085444 0.387279173 6 0.611162157 -0.800341491 7 0.874152127 -0.309489209 8 0.626770495 -0.451526862 9 0.391686754 -0.257575828 10 1.051380786 -0.441363207 11 0.388223865 0.102570973 12 0.584886995 -0.180795431 13 1.354252705 0.178986665 14 0.254552614 0.190503429 15 0.576676539 -0.725386446 16 0.541465658 -0.441851913 17 0.224092525 -0.979257291 18 -0.400843100 -1.708943425 19 -0.042203330 -0.511224778 20 1.543064764 -1.787948608 21 -0.641386598 -0.677150018 22 1.465448381 -0.028458620 23 1.067146304 -1.112052263 24 0.237099938 0.031586593 25 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1.238447013 2.463937981 > postscript(file="/var/wessaorg/rcomp/tmp/18vpg1335791149.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > fa.diagram(fit) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2j2hd1335791149.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(fs,pch=20) > text(fs,labels=rownames(y),pos=3) > dev.off() null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/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="/var/wessaorg/rcomp/tmp/393j81335791149.tab") > > try(system("convert tmp/18vpg1335791149.ps tmp/18vpg1335791149.png",intern=TRUE)) character(0) > try(system("convert tmp/2j2hd1335791149.ps tmp/2j2hd1335791149.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.936 0.172 1.103