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Type 'q()' to quit R. > par5 = 'ATTLES separate' > par4 = 'all' > par3 = 'all' > par2 = 'all' > par1 = '2' > par5 <- 'ATTLES separate' > 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 A11 0.56 -0.40 0.47 0.53 A12 0.12 0.72 0.52 0.48 A13 -0.09 0.56 0.33 0.67 A14 0.23 0.54 0.35 0.65 A15 0.61 0.05 0.37 0.63 A16 0.63 -0.28 0.47 0.53 A17 0.42 0.17 0.21 0.79 A18 0.54 0.22 0.35 0.65 A19 0.42 0.44 0.37 0.63 A20 0.50 0.22 0.30 0.70 RC1 RC2 SS loadings 2.04 1.69 Proportion Var 0.20 0.17 Cumulative Var 0.20 0.37 Test of the hypothesis that 2 factors are sufficient. The degrees of freedom for the null model are 45 and the objective function was 0.89 The degrees of freedom for the model are 26 and the objective function was 0.44 The number of observations was 996 with Chi Square = 433.03 with prob < 2.2e-75 Fit based upon off diagonal values = 0.51> fs <- factor.scores(y,fit) > fs RC1 RC2 1 -1.0892969156 -1.961907117 2 1.6443951780 0.650015005 3 -1.3046928705 -0.742042495 4 0.9752027095 -0.846117098 5 -0.5806732734 -1.296517693 6 0.9620772550 -0.413566256 7 0.1288817600 0.118075003 8 0.0368500635 -1.908439381 9 0.4135796407 -0.660600970 10 1.4214147447 0.264049741 11 0.4139678908 -1.777696870 12 1.0844843201 0.682792247 13 0.7230769627 -1.207351590 14 1.0623688884 -0.192490930 15 -0.5587249187 0.247656998 16 -0.0007783953 -0.353954319 17 1.1462289259 0.518312964 18 0.4138252189 -0.184687589 19 0.6944432166 -1.213334188 20 0.4345455182 -0.629656605 21 0.1989460152 -0.026487259 22 -0.8422088070 -0.845620366 23 1.4256512384 -0.150713902 24 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1.2355284454 1.072844148 957 0.0490036565 -0.578409512 958 -0.1093697764 -0.399463161 959 -0.3153967480 0.995724138 960 -0.8684383916 0.189022023 961 -0.8413342048 1.417944875 962 -0.6225633112 1.508198429 963 1.1629001785 0.340290045 964 -1.1021114619 1.243875622 965 -0.3940030659 1.925026458 966 0.2925018971 0.159938661 967 0.4994720638 1.836998610 968 0.5083585563 1.814466303 969 -1.6960731471 1.341555732 970 -2.1310679310 0.174580257 971 -0.5264825992 0.979659112 972 -1.7874247445 1.225814120 973 -0.5178724175 0.686680477 974 -0.3776703050 -0.353543977 975 -0.5212815868 0.794119504 976 -0.0313892924 1.312254140 977 -1.8121730965 0.027524439 978 0.5182999789 1.766001710 979 -0.5177785348 1.218508962 980 -0.0313571125 2.012918446 981 -0.6798998592 1.248657344 982 -0.1515371212 -1.823327110 983 -0.0989754618 -1.816586163 984 -0.2068984567 -2.855644792 985 -1.0313374920 0.211576969 986 -0.9753368481 0.922567002 987 0.2742687440 1.148037017 988 -0.1081322005 0.688466794 989 -1.6954259329 -3.374809671 990 -0.0194368700 -0.330467359 991 0.9678006815 1.240521737 992 -0.7704057440 1.399666159 993 -0.7054405362 -0.150322125 994 -1.8566981410 1.008997596 995 -0.0250805920 1.129051913 996 1.0870464538 2.335293465 > postscript(file="/var/www/rcomp/tmp/1k2501336494067.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/www/rcomp/tmp/2mqrd1336494067.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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/www/rcomp/tmp/3szqy1336494067.tab") > > try(system("convert tmp/1k2501336494067.ps tmp/1k2501336494067.png",intern=TRUE)) character(0) > try(system("convert tmp/2mqrd1336494067.ps tmp/2mqrd1336494067.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.850 0.560 2.434