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Type 'q()' to quit R. > par5 = 'ATTLES all' > par4 = 'all' > par3 = 'all' > par2 = 'all' > par1 = '2' > par5 <- 'ATTLES all' > par4 <- 'all' > par3 <- 'all' > par2 <- 'all' > 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 0.53 0.01 0.28 0.72 A2 -0.18 0.57 0.36 0.64 A3 0.52 0.14 0.29 0.71 A4 0.04 0.49 0.24 0.76 A5 0.24 0.35 0.18 0.82 A6 0.49 0.24 0.29 0.71 A7 0.20 0.45 0.24 0.76 A8 0.40 0.48 0.39 0.61 A9 0.05 0.50 0.25 0.75 A10 0.46 0.21 0.26 0.74 A11 0.53 -0.47 0.50 0.50 A12 0.11 0.57 0.33 0.67 A13 0.04 0.40 0.16 0.84 A14 0.21 0.44 0.23 0.77 A15 0.61 0.00 0.37 0.63 A16 0.50 -0.26 0.32 0.68 A17 0.39 0.13 0.17 0.83 A18 0.50 0.05 0.25 0.75 A19 0.41 0.31 0.26 0.74 A20 0.35 0.16 0.15 0.85 RC1 RC2 SS loadings 2.95 2.58 Proportion Var 0.15 0.13 Cumulative Var 0.15 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 2.66 The degrees of freedom for the model are 151 and the objective function was 0.81 The number of observations was 993 with Chi Square = 795.78 with prob < 3.3e-88 Fit based upon off diagonal values = 0.77> fs <- factor.scores(y,fit) > fs RC1 RC2 1 -0.3900926902 -1.356964876 2 2.2148267970 -0.349481410 3 -1.2011201136 0.657377673 4 0.2832994262 -1.425239950 5 -0.9206543380 -1.732509247 6 0.4688408895 -0.040263404 7 -0.1727661909 -0.493404829 8 0.0293952407 -1.341045224 9 0.8850015119 -0.490027237 10 0.5581622129 -0.131128175 11 -1.0030585743 -1.358906245 12 1.2729685815 0.223843065 13 0.3238106404 -0.624411340 14 0.9053195236 -0.372523861 15 0.0821152785 0.757080502 16 0.2699050057 -0.737909117 17 0.9572052565 0.373471822 18 0.3635431823 -0.218822198 19 0.3280372187 -1.325504041 20 0.8008618022 -0.776633137 21 0.0873812933 0.131971001 22 -0.5002645885 -1.225100309 23 1.0236147676 -0.493642751 24 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-0.5770091578 -0.015882496 991 -1.4008293782 1.101889519 992 0.1624076903 0.679034336 993 1.2972724174 2.809482894 > postscript(file="/var/wessaorg/rcomp/tmp/1z0jk1335801732.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/2ma7a1335801732.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/322791335801732.tab") > > try(system("convert tmp/1z0jk1335801732.ps tmp/1z0jk1335801732.png",intern=TRUE)) character(0) > try(system("convert tmp/2ma7a1335801732.ps tmp/2ma7a1335801732.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.148 0.189 1.327