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Type 'q()' to quit R. > par5 = 'Learning Activities' > par4 = 'all' > par3 = 'all' > par2 = 'all' > par1 = '2' > par5 <- 'Learning Activities' > 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 BC 0.26 0.72 0.59 0.414 NNZFG 0.09 0.59 0.36 0.641 MRT 0.21 0.36 0.18 0.822 AFL 0.93 0.14 0.89 0.114 LPM 0.94 0.20 0.93 0.072 LPC 0.83 0.23 0.74 0.264 W 0.09 0.74 0.55 0.447 WPA 0.11 0.66 0.45 0.550 RC1 RC2 SS loadings 2.58 2.09 Proportion Var 0.32 0.26 Cumulative Var 0.32 0.58 Test of the hypothesis that 2 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 13 and the objective function was 0.79 The number of observations was 558 with Chi Square = 436.15 with prob < 5.1e-85 Fit based upon off diagonal values = 0.9> fs <- factor.scores(y,fit) > fs RC1 RC2 1 0.368328210 0.492144003 2 2.405031107 0.421212294 3 0.637395238 0.746129115 4 -0.639049280 0.401045635 5 0.862416602 -0.148362779 6 1.466174099 -0.489931377 7 -0.513540407 0.346342123 8 0.078801381 0.635179888 9 2.630949618 -0.903861196 10 1.762175958 2.062493779 11 -0.343718634 0.729937560 12 -0.049203036 -0.388026306 13 -0.299218694 -0.322896073 14 0.727959838 0.624357553 15 -0.948554934 1.280345422 16 1.184991066 0.062277205 17 0.338012462 0.759711561 18 1.148409583 -0.417010385 19 -0.698573655 0.297411558 20 -0.355959237 0.683465670 21 -0.671193106 0.960450633 22 0.467723799 0.419745746 23 0.093188754 1.669708619 24 0.176674714 1.077363805 25 0.765177107 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508 -0.701222016 0.280899424 509 -0.529212139 0.256581407 510 -0.781491493 -1.236810845 511 -1.160353385 1.964553987 512 -0.403097295 -2.400206135 513 -0.655782004 -1.620992596 514 -0.197671411 -0.661921817 515 -0.152485728 -1.817749224 516 -1.061865475 -0.523408346 517 -0.867719902 -1.909412557 518 -0.820181963 0.595040708 519 -0.687833044 -0.492544213 520 0.041712994 -2.425532708 521 -0.374043122 -2.175959109 522 -0.499180767 0.118113341 523 -0.674811688 -0.772056456 524 -0.756636550 -0.653152342 525 -0.552939694 0.035710167 526 -0.588303900 -0.980032241 527 -0.811212283 -1.150130597 528 -0.310443867 -1.082043803 529 -0.918924699 -0.238341947 530 0.015195538 1.399137267 531 0.684092067 -1.473333558 532 -0.704907195 -0.241308457 533 -1.001788952 -0.275892060 534 -0.247475599 0.238713864 535 0.167288653 -0.755077471 536 1.071425758 0.046582150 537 -0.600825290 -0.011730997 538 0.088004441 -0.664084489 539 -0.517897248 -0.569529519 540 -0.786410447 -1.272220050 541 -1.320182339 -2.978162618 542 -0.632474124 -0.442575558 543 -0.087293096 0.642138257 544 -0.336221985 -0.269328438 545 -0.171064094 0.460408726 546 -0.608653939 0.691709396 547 -0.483665187 -1.235539660 548 -0.155568433 -1.259062269 549 -0.047131232 -2.828387816 550 -0.248810059 -0.372325243 551 -1.027265990 -0.883971505 552 0.022415319 -0.941568779 553 -0.403089662 0.062542365 554 -0.790968821 -0.343687009 555 -1.083992852 -2.638348272 556 -0.803242973 -0.467560320 557 -0.417967041 -0.770318204 558 -0.390722751 -0.603495436 > postscript(file="/var/wessaorg/rcomp/tmp/1eufw1337248148.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/29i1y1337248148.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/3dlbr1337248148.tab") > > try(system("convert tmp/1eufw1337248148.ps tmp/1eufw1337248148.png",intern=TRUE)) character(0) > try(system("convert tmp/29i1y1337248148.ps tmp/29i1y1337248148.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.959 0.237 1.190