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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_factor_analysisdm.wasp
Title produced by softwareFactor Analysis
Date of computationTue, 01 May 2012 10:48:15 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/01/t1335883707egmpv2hsm0r7o1r.htm/, Retrieved Sat, 04 May 2024 19:38:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165624, Retrieved Sat, 04 May 2024 19:38:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [female-bachelor] [2012-05-01 14:48:15] [c38c32477296496b546025b407c5c736] [Current]
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Dataset

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'AstonUniversity' @ aston.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165624&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165624&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165624&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'AstonUniversity' @ aston.wessa.net






Rotated Factor Loadings
VariablesFactor1Factor2
U10.5790.559
U20.5970.477
U30.390.462
U40.6830.294
U50.3870.516
U60.5020.468
U70.5920.412
U80.4250.217
U90.5040.364
U10-0.2270.44
U110.0660.262
U12-0.1620.527
U130.0560.611
U140.0850.416
U150.10.614
U160.170.506
U170.2340.558
U180.3060.564
U190.3490.454
U200.5570.508
U210.76-0.036
U220.722-0.068
U230.6080.193
U240.6320.23
U25-0.433-0.525
U260.1430.32
U270.5840.123
U280.742-0.064
U290.410.318
U300.2960.582
U310.2740.41
U320.1390.36
U330.1640.227

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
U1 & 0.579 & 0.559 \tabularnewline
U2 & 0.597 & 0.477 \tabularnewline
U3 & 0.39 & 0.462 \tabularnewline
U4 & 0.683 & 0.294 \tabularnewline
U5 & 0.387 & 0.516 \tabularnewline
U6 & 0.502 & 0.468 \tabularnewline
U7 & 0.592 & 0.412 \tabularnewline
U8 & 0.425 & 0.217 \tabularnewline
U9 & 0.504 & 0.364 \tabularnewline
U10 & -0.227 & 0.44 \tabularnewline
U11 & 0.066 & 0.262 \tabularnewline
U12 & -0.162 & 0.527 \tabularnewline
U13 & 0.056 & 0.611 \tabularnewline
U14 & 0.085 & 0.416 \tabularnewline
U15 & 0.1 & 0.614 \tabularnewline
U16 & 0.17 & 0.506 \tabularnewline
U17 & 0.234 & 0.558 \tabularnewline
U18 & 0.306 & 0.564 \tabularnewline
U19 & 0.349 & 0.454 \tabularnewline
U20 & 0.557 & 0.508 \tabularnewline
U21 & 0.76 & -0.036 \tabularnewline
U22 & 0.722 & -0.068 \tabularnewline
U23 & 0.608 & 0.193 \tabularnewline
U24 & 0.632 & 0.23 \tabularnewline
U25 & -0.433 & -0.525 \tabularnewline
U26 & 0.143 & 0.32 \tabularnewline
U27 & 0.584 & 0.123 \tabularnewline
U28 & 0.742 & -0.064 \tabularnewline
U29 & 0.41 & 0.318 \tabularnewline
U30 & 0.296 & 0.582 \tabularnewline
U31 & 0.274 & 0.41 \tabularnewline
U32 & 0.139 & 0.36 \tabularnewline
U33 & 0.164 & 0.227 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165624&T=1

[TABLE]
[ROW][C]Rotated Factor Loadings[/C][/ROW]
[ROW][C]Variables[/C][C]Factor1[/C][C]Factor2[/C][/ROW]
[ROW][C]U1[/C][C]0.579[/C][C]0.559[/C][/ROW]
[ROW][C]U2[/C][C]0.597[/C][C]0.477[/C][/ROW]
[ROW][C]U3[/C][C]0.39[/C][C]0.462[/C][/ROW]
[ROW][C]U4[/C][C]0.683[/C][C]0.294[/C][/ROW]
[ROW][C]U5[/C][C]0.387[/C][C]0.516[/C][/ROW]
[ROW][C]U6[/C][C]0.502[/C][C]0.468[/C][/ROW]
[ROW][C]U7[/C][C]0.592[/C][C]0.412[/C][/ROW]
[ROW][C]U8[/C][C]0.425[/C][C]0.217[/C][/ROW]
[ROW][C]U9[/C][C]0.504[/C][C]0.364[/C][/ROW]
[ROW][C]U10[/C][C]-0.227[/C][C]0.44[/C][/ROW]
[ROW][C]U11[/C][C]0.066[/C][C]0.262[/C][/ROW]
[ROW][C]U12[/C][C]-0.162[/C][C]0.527[/C][/ROW]
[ROW][C]U13[/C][C]0.056[/C][C]0.611[/C][/ROW]
[ROW][C]U14[/C][C]0.085[/C][C]0.416[/C][/ROW]
[ROW][C]U15[/C][C]0.1[/C][C]0.614[/C][/ROW]
[ROW][C]U16[/C][C]0.17[/C][C]0.506[/C][/ROW]
[ROW][C]U17[/C][C]0.234[/C][C]0.558[/C][/ROW]
[ROW][C]U18[/C][C]0.306[/C][C]0.564[/C][/ROW]
[ROW][C]U19[/C][C]0.349[/C][C]0.454[/C][/ROW]
[ROW][C]U20[/C][C]0.557[/C][C]0.508[/C][/ROW]
[ROW][C]U21[/C][C]0.76[/C][C]-0.036[/C][/ROW]
[ROW][C]U22[/C][C]0.722[/C][C]-0.068[/C][/ROW]
[ROW][C]U23[/C][C]0.608[/C][C]0.193[/C][/ROW]
[ROW][C]U24[/C][C]0.632[/C][C]0.23[/C][/ROW]
[ROW][C]U25[/C][C]-0.433[/C][C]-0.525[/C][/ROW]
[ROW][C]U26[/C][C]0.143[/C][C]0.32[/C][/ROW]
[ROW][C]U27[/C][C]0.584[/C][C]0.123[/C][/ROW]
[ROW][C]U28[/C][C]0.742[/C][C]-0.064[/C][/ROW]
[ROW][C]U29[/C][C]0.41[/C][C]0.318[/C][/ROW]
[ROW][C]U30[/C][C]0.296[/C][C]0.582[/C][/ROW]
[ROW][C]U31[/C][C]0.274[/C][C]0.41[/C][/ROW]
[ROW][C]U32[/C][C]0.139[/C][C]0.36[/C][/ROW]
[ROW][C]U33[/C][C]0.164[/C][C]0.227[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165624&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165624&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Rotated Factor Loadings
VariablesFactor1Factor2
U10.5790.559
U20.5970.477
U30.390.462
U40.6830.294
U50.3870.516
U60.5020.468
U70.5920.412
U80.4250.217
U90.5040.364
U10-0.2270.44
U110.0660.262
U12-0.1620.527
U130.0560.611
U140.0850.416
U150.10.614
U160.170.506
U170.2340.558
U180.3060.564
U190.3490.454
U200.5570.508
U210.76-0.036
U220.722-0.068
U230.6080.193
U240.6320.23
U25-0.433-0.525
U260.1430.32
U270.5840.123
U280.742-0.064
U290.410.318
U300.2960.582
U310.2740.41
U320.1390.36
U330.1640.227


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ; par2 = female ; par3 = bachelor ; par4 = all ; par5 = ATTLES separate ;
Parameters (R input):
par1 = 2 ; par2 = female ; par3 = bachelor ; par4 = all ; par5 = CSUQ ;
R code (references can be found in the software module):
library(psych)
x <- as.data.frame(read.table(file='https://automated.biganalytics.eu/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$Year==as.numeric(par4),]
}
cAc <- with(x,cbind( A1, A2, A3, A4, A5, A6, A7, A8, A9,A10))
cAs <- with(x,cbind(A11,A12,A13,A14,A15,A16,A17,A18,A19,A20))
cA <- cbind(cAc,cAs)
cCa <- with(x,cbind(C1,C3,C5,C7, C9,C11,C13,C15,C17,C19,C21,C23,C25,C27,C29,C31,C33,C35,C37,C39,C41,C43,C45,C47))
cCp <- with(x,cbind(C2,C4,C6,C8,C10,C12,C14,C16,C18,C20,C22,C24,C26,C28,C30,C32,C34,C36,C38,C40,C42,C44,C46,C48))
cC <- cbind(cCa,cCp)
cU <- with(x,cbind(U1,U2,U3,U4,U5,U6,U7,U8,U9,U10,U11,U12,U13,U14,U15,U16,U17,U18,U19,U20,U21,U22,U23,U24,U25,U26,U27,U28,U29,U30,U31,U32,U33))
cE <- with(x,cbind(BC,NNZFG,MRT,AFL,LPM,LPC,W,WPA))
cX <- with(x,cbind(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18))
if (par5=='ATTLES connected') x <- cAc
if (par5=='ATTLES separate') x <- cAs
if (par5=='ATTLES all') x <- cA
if (par5=='COLLES actuals') x <- cCa
if (par5=='COLLES preferred') x <- cCp
if (par5=='COLLES all') x <- cC
if (par5=='CSUQ') x <- cU
if (par5=='Learning Activities') x <- cE
if (par5=='Exam Items') x <- cX
ncol <- length(x[1,])
for (jjj in 1:ncol) {
x <- x[!is.na(x[,jjj]),]
}
par1 <- as.numeric(par1)
nrows <- length(x[,1])
rownames(x) <- 1:nrows
y <- x
fit <- principal(y, nfactors=par1, rotate='varimax')
fit
fs <- factor.scores(y,fit)
fs
bitmap(file='test1.png')
fa.diagram(fit)
dev.off()
bitmap(file='test2.png')
plot(fs,pch=20)
text(fs,labels=rownames(y),pos=3)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Rotated Factor Loadings',par1+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variables',1,TRUE)
for (i in 1:par1) {
a<-table.element(a,paste('Factor',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (j in 1:length(fit$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='mytable.tab')