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Type 'q()' to quit R. > par5 = 'Learning Activities' > par4 = 'all' > par3 = 'all' > par2 = 'all' > par1 = '3' > par5 <- 'Learning Activities' > par4 <- 'all' > par3 <- 'all' > par2 <- 'all' > par1 <- '3' > #'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 RC3 h2 u2 BC 0.24 0.43 0.61 0.62 0.378 NNZFG 0.03 0.07 0.86 0.75 0.255 MRT 0.17 -0.04 0.63 0.43 0.569 AFL 0.93 0.12 0.09 0.89 0.107 LPM 0.95 0.19 0.10 0.94 0.059 LPC 0.81 0.10 0.27 0.74 0.257 W 0.11 0.84 0.14 0.73 0.268 WPA 0.15 0.85 -0.01 0.75 0.252 RC1 RC2 RC3 SS loadings 2.55 1.68 1.63 Proportion Var 0.32 0.21 0.20 Cumulative Var 0.32 0.53 0.73 Test of the hypothesis that 3 factors are sufficient. The degrees of freedom for the null model are 28 and the objective function was 3.9 The degrees of freedom for the model are 7 and the objective function was 0.76 The number of observations was 558 with Chi Square = 419.27 with prob < 1.8e-86 Fit based upon off diagonal values = 0.94> fs <- factor.scores(y,fit) > fs RC1 RC2 RC3 1 0.4001653741 0.684459903 -0.061702521 2 2.3192937694 -0.321630230 1.137361727 3 0.5960327167 0.337813878 0.788785673 4 -0.5700235043 0.905573846 -0.509670313 5 0.8806690372 -0.001498609 -0.216485281 6 1.5057097546 -0.149170054 -0.565551065 7 -0.5832639175 -0.226902039 0.830070477 8 0.0124127673 0.050353302 0.959165789 9 2.6358092267 -0.805100136 -0.378438730 10 1.6238712252 0.746913529 2.415534968 11 -0.5103039958 -0.640687535 1.970992109 12 0.0051651148 0.076949706 -0.721477834 13 -0.2612802994 0.010349339 -0.538839747 14 0.5261004740 -1.023875197 2.308306908 15 -0.9428604547 1.203368212 0.521457866 16 1.1432078551 -0.285006083 0.486161482 17 0.1627076463 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-0.7796391316 1.497716400 -2.350836166 534 -0.1391656999 1.061512053 -0.957607494 535 0.1708432566 -0.650816002 -0.390692665 536 1.2155783187 1.152185684 -1.349779215 537 -0.5445230471 0.436104958 -0.581458291 538 0.1297132344 -0.270795827 -0.724406613 539 -0.4940374140 -0.317599436 -0.527659207 540 -0.6630724877 -0.168017656 -1.851248142 541 -1.2255419906 -1.913252263 -2.409341386 542 -0.5860403168 -0.026403091 -0.692660507 543 0.0539037216 1.677314182 -1.080335087 544 -0.3917014249 -0.669611051 0.401814222 545 -0.0894778627 1.050769477 -0.586071638 546 -0.5578223100 1.023705533 -0.190508376 547 -0.4245364973 -0.639654591 -1.191921873 548 -0.1371405473 -0.982238766 -0.791104816 549 -0.0259614128 -2.368068866 -1.566899673 550 -0.1764649254 0.233714600 -0.898105454 551 -0.9780431457 -0.395072675 -0.947309732 552 0.1432262517 0.098247998 -1.636106623 553 -0.3059446849 0.818605468 -0.938723787 554 -0.7607054861 -0.061898382 -0.492781470 555 -0.9808626987 -1.545629220 -2.320293751 556 -0.6758988781 0.584265424 -1.505037514 557 -0.3489387651 -0.146538910 -1.063194113 558 -0.3957800560 -0.575114544 -0.255314164 > postscript(file="/var/wessaorg/rcomp/tmp/1kw2t1337757351.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/2joxx1337757351.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/3a31y1337757351.tab") > > try(system("convert tmp/1kw2t1337757351.ps tmp/1kw2t1337757351.png",intern=TRUE)) character(0) > try(system("convert tmp/2joxx1337757351.ps tmp/2joxx1337757351.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.911 0.194 1.102