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Type 'q()' to quit R. > par5 = 'ATTLES connected' > par4 = 'all' > par3 = 'all' > par2 = 'all' > par1 = '2' > par5 <- 'ATTLES connected' > 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 0.56 -0.11 0.33 0.67 A2 -0.13 0.73 0.54 0.46 A3 0.65 0.02 0.42 0.58 A4 0.24 0.45 0.26 0.74 A5 0.49 0.11 0.26 0.74 A6 0.63 0.10 0.41 0.59 A7 0.28 0.50 0.33 0.67 A8 0.58 0.33 0.45 0.55 A9 0.01 0.69 0.48 0.52 A10 0.52 0.15 0.29 0.71 RC1 RC2 SS loadings 2.14 1.62 Proportion Var 0.21 0.16 Cumulative Var 0.21 0.38 Test of the hypothesis that 2 factors are sufficient. The degrees of freedom for the null model are 45 and the objective function was 0.98 The degrees of freedom for the model are 26 and the objective function was 0.46 The number of observations was 1005 with Chi Square = 462.13 with prob < 2.3e-81 Fit based upon off diagonal values = 0.6> fs <- factor.scores(y,fit) > fs RC1 RC2 1 0.361761795 -0.832402250 2 1.794579294 -1.237048338 3 0.036036727 0.982342098 4 -0.810599509 -0.961814117 5 -1.409611775 -1.128540052 6 -0.026384558 0.415267771 7 -0.732483151 -0.504025633 8 -0.076153985 -0.530947924 9 1.229253393 -0.729297586 10 -0.477322377 -0.088366575 11 -2.522187900 0.476867912 12 1.185209452 -0.543756925 13 -0.190486560 0.276783875 14 0.095069212 0.097130402 15 1.344604370 0.072376464 16 0.315525496 -1.008353573 17 0.754497067 -0.102041322 18 0.122069915 -0.026031734 19 -0.120404239 -1.172931767 20 0.883238093 -0.979817676 21 -0.451571556 0.956722494 22 0.201855822 -2.009000047 23 0.256310561 -0.483350739 24 -1.411594745 0.687052421 25 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0.146379736 957 1.496215786 0.537272082 958 0.887473595 0.552470745 959 -1.883497264 0.926256431 960 -0.471697513 1.297076286 961 0.341148032 0.361704093 962 -1.761438569 -1.039209570 963 0.472944225 1.202193768 964 0.679173957 1.460298647 965 -0.008661250 2.128879720 966 -0.090402192 -0.123964014 967 -1.065765206 -0.099791418 968 -0.112083852 -0.499530453 969 0.744946821 0.828584553 970 -0.167410885 0.589812307 971 -0.939577403 0.873168199 972 -0.970772960 1.188339807 973 -2.291451418 1.269866539 974 0.950922574 2.273190131 975 -2.060589421 0.710912368 976 1.271645417 1.281077276 977 -0.128637112 1.455522010 978 -0.916435748 0.369410204 979 -1.323465434 1.346624590 980 0.573047561 1.168126765 981 -0.833286373 0.600483656 982 -0.753266202 1.170629583 983 -0.383417803 1.335371899 984 -0.558960364 -0.125094586 985 -0.095251081 1.029042420 986 -1.145279502 0.451834922 987 0.583033881 1.291087222 988 -0.462615559 1.448161654 989 -0.091481173 1.937999980 990 -0.559162328 -0.713262141 991 -1.928976727 -0.082271593 992 -0.453363214 -1.043955969 993 -4.089456858 -0.353874463 994 -0.649730005 0.280635288 995 -2.042372498 0.302081674 996 -0.065430995 0.502048510 997 -0.710511542 -1.347349553 998 -3.764700954 -1.481079812 999 -0.675582877 -0.715122377 1000 1.274842639 2.685713804 1001 -0.554552002 -0.329438694 1002 -0.372979162 0.270895279 1003 -0.383772853 0.778556842 1004 0.463291025 -0.083296079 1005 1.385996061 2.448870293 > postscript(file="/var/wessaorg/rcomp/tmp/1rfik1335806164.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/2rtxc1335806164.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/3jqg01335806164.tab") > > try(system("convert tmp/1rfik1335806164.ps tmp/1rfik1335806164.png",intern=TRUE)) character(0) > try(system("convert tmp/2rtxc1335806164.ps tmp/2rtxc1335806164.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.214 0.257 1.467