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Type 'q()' to quit R. > par5 = 'ATTLES separate' > par4 = 'all' > par3 = 'all' > par2 = 'male' > par1 = '2' > par5 <- 'ATTLES separate' > par4 <- 'all' > par3 <- 'all' > par2 <- 'male' > 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 -0.11 0.58 0.35 0.65 A12 0.70 -0.03 0.49 0.51 A13 0.61 -0.36 0.51 0.49 A14 0.48 0.19 0.27 0.73 A15 0.35 0.43 0.31 0.69 A16 -0.11 0.72 0.53 0.47 A17 0.22 0.42 0.22 0.78 A18 0.45 0.33 0.31 0.69 A19 0.63 0.09 0.40 0.60 A20 0.28 0.54 0.38 0.62 RC1 RC2 SS loadings 1.97 1.79 Proportion Var 0.20 0.18 Cumulative Var 0.20 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 0.9 The degrees of freedom for the model are 26 and the objective function was 0.42 The number of observations was 545 with Chi Square = 228.48 with prob < 2.8e-34 Fit based upon off diagonal values = 0.55> fs <- factor.scores(y,fit) > fs RC1 RC2 1 -1.6785916089 -0.237680249 2 -0.2722869112 1.191241606 3 -0.4282043960 0.460414806 4 0.5906487123 1.248317660 5 0.9814146944 0.663780935 6 -0.9773467146 1.163719373 7 0.2593698917 0.795199929 8 -0.2232534481 0.603082703 9 -0.1072147466 0.187158683 10 0.2456531265 1.445658367 11 0.7312148601 0.153130803 12 -0.4800964051 1.198126444 13 0.4221331073 1.721963378 14 -0.6506380563 0.418733450 15 -0.6767382496 0.753585925 16 0.2410356020 0.895536666 17 -1.2332742563 0.385241011 18 -1.2666500849 0.015424377 19 -0.2197127232 -0.103005046 20 -0.2282279703 0.967904941 21 -0.8937603071 0.159807068 22 0.2593698917 0.795199929 23 -0.3901851666 0.348520169 24 0.8380371708 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-1.454003376 459 0.6756069078 -1.514354271 460 1.5134229632 0.634216994 461 0.0834106254 -0.048041671 462 0.9624031772 0.434376933 463 0.3994280008 0.040989844 464 -1.0432015872 -0.065178723 465 2.2383925083 1.374219863 466 0.1274383376 -0.540592666 467 0.4065443980 0.395772757 468 0.0961714173 -0.690915923 469 1.0494618143 -0.167056125 470 0.3967092731 -1.053818803 471 0.9834323297 -0.315702496 472 0.4512201858 -0.534833931 473 -0.3929067769 -1.501882671 474 0.5883534435 -0.400018009 475 -0.0638329331 0.311546084 476 1.8639836334 -0.643284785 477 0.1267978621 -1.674623505 478 0.5559872177 -1.290932282 479 1.5651990661 -0.420625090 480 0.7690169085 -0.399487810 481 -0.3657457666 -1.112871605 482 -0.2511208387 -0.863762108 483 -0.6607332251 -1.759207763 484 1.2987648063 1.197092115 485 -0.1600327483 -1.198776934 486 0.3944112277 -0.759148750 487 -0.2014636193 0.674015081 488 -0.3207264672 -1.208585659 489 -0.2139895664 -0.983382331 490 1.5792596343 0.840980798 491 0.3001815568 -2.055322663 492 -0.7409401602 0.873511798 493 -0.5544984287 -0.917596338 494 1.3901025366 -1.121038211 495 0.4833979408 0.526226027 496 -0.5711238541 -0.659541455 497 0.2191324353 0.358995546 498 0.0692759533 -1.140676028 499 0.7693930362 -0.686049329 500 0.9505069152 1.696567383 501 -2.4381336725 -1.529030617 502 0.6913626894 0.031040986 503 1.3246122597 0.262684812 504 -0.2217222392 2.031828836 505 1.6577159022 -0.205563456 506 1.9647529267 -0.746962877 507 2.6635049997 0.065795411 508 0.9204231255 -0.852432157 509 1.8896634045 1.320567610 510 1.3731510655 -2.091631843 511 0.7462618797 -1.491918341 512 -0.4890988182 0.691240017 513 0.4366409194 -1.455455160 514 -0.5757994201 -1.776470606 515 0.2714921690 -1.721271079 516 2.0741753068 -1.182314439 517 -0.2027410308 -1.094578678 518 -0.0589273272 -0.207022671 519 0.9222110638 -0.515460581 520 -1.4199709974 -0.585432298 521 0.4103100807 -0.625193096 522 -0.2245945955 -2.073719104 523 1.4324687983 -0.254006799 524 0.6240300217 -0.497068221 525 0.7941372121 -1.075092849 526 0.9260366217 0.517460417 527 0.0816971536 0.341769612 528 1.7563110472 -0.226435446 529 0.5898710341 -2.095873259 530 -0.5874985500 -2.105495599 531 0.5239320271 -0.857301161 532 0.6525133948 -0.607733022 533 1.6987336863 -0.692179450 534 0.9746819674 -1.185416747 535 -1.6480812785 0.256009150 536 0.4880442268 -1.428943406 537 0.9688248312 0.040040647 538 0.6500275875 -0.463756485 539 -3.7377351146 -0.543802837 540 -0.2903957629 -0.095910487 541 1.4852674912 0.236062639 542 1.3078062996 -1.722176136 543 0.3111349926 -2.170586798 544 0.9370405880 -0.434154897 545 2.1819788283 0.476527804 > postscript(file="/var/wessaorg/rcomp/tmp/1hvj21335883766.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/2220w1335883766.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/3a12h1335883766.tab") > > try(system("convert tmp/1hvj21335883766.ps tmp/1hvj21335883766.png",intern=TRUE)) character(0) > try(system("convert tmp/2220w1335883766.ps tmp/2220w1335883766.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.109 0.266 1.369