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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 computationWed, 29 Aug 2012 10:40:00 -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/Aug/29/t1346251275npos39j6ivi3kay.htm/, Retrieved Sun, 05 May 2024 15:31:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169563, Retrieved Sun, 05 May 2024 15:31:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [Factor analysis] [2012-08-29 14:40:00] [b55bb772a6f26e603d6586329563b02f] [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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169563&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169563&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169563&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Rotated Factor Loadings
VariablesFactor1Factor2
U10.6790.466
U20.6650.467
U30.6490.369
U40.5350.486
U50.5890.405
U60.6170.405
U70.5850.471
U80.4470.383
U90.4530.485
U100.398-0.002
U110.3750.273
U120.5590.098
U130.610.215
U140.4860.258
U150.560.314
U160.6460.173
U170.60.178
U180.6240.24
U190.520.305
U200.7090.467
U210.1660.809
U220.2210.815
U230.1960.767
U240.2360.744
U25-0.449-0.455
U260.3220.11
U270.3770.325
U280.1350.772
U290.2560.731
U300.5140.538
U310.5470.459
U320.530.101
U330.3930.115

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
U1 & 0.679 & 0.466 \tabularnewline
U2 & 0.665 & 0.467 \tabularnewline
U3 & 0.649 & 0.369 \tabularnewline
U4 & 0.535 & 0.486 \tabularnewline
U5 & 0.589 & 0.405 \tabularnewline
U6 & 0.617 & 0.405 \tabularnewline
U7 & 0.585 & 0.471 \tabularnewline
U8 & 0.447 & 0.383 \tabularnewline
U9 & 0.453 & 0.485 \tabularnewline
U10 & 0.398 & -0.002 \tabularnewline
U11 & 0.375 & 0.273 \tabularnewline
U12 & 0.559 & 0.098 \tabularnewline
U13 & 0.61 & 0.215 \tabularnewline
U14 & 0.486 & 0.258 \tabularnewline
U15 & 0.56 & 0.314 \tabularnewline
U16 & 0.646 & 0.173 \tabularnewline
U17 & 0.6 & 0.178 \tabularnewline
U18 & 0.624 & 0.24 \tabularnewline
U19 & 0.52 & 0.305 \tabularnewline
U20 & 0.709 & 0.467 \tabularnewline
U21 & 0.166 & 0.809 \tabularnewline
U22 & 0.221 & 0.815 \tabularnewline
U23 & 0.196 & 0.767 \tabularnewline
U24 & 0.236 & 0.744 \tabularnewline
U25 & -0.449 & -0.455 \tabularnewline
U26 & 0.322 & 0.11 \tabularnewline
U27 & 0.377 & 0.325 \tabularnewline
U28 & 0.135 & 0.772 \tabularnewline
U29 & 0.256 & 0.731 \tabularnewline
U30 & 0.514 & 0.538 \tabularnewline
U31 & 0.547 & 0.459 \tabularnewline
U32 & 0.53 & 0.101 \tabularnewline
U33 & 0.393 & 0.115 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169563&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]0.679[/C][C]0.466[/C][/ROW]
[ROW][C]U2[/C][C]0.665[/C][C]0.467[/C][/ROW]
[ROW][C]U3[/C][C]0.649[/C][C]0.369[/C][/ROW]
[ROW][C]U4[/C][C]0.535[/C][C]0.486[/C][/ROW]
[ROW][C]U5[/C][C]0.589[/C][C]0.405[/C][/ROW]
[ROW][C]U6[/C][C]0.617[/C][C]0.405[/C][/ROW]
[ROW][C]U7[/C][C]0.585[/C][C]0.471[/C][/ROW]
[ROW][C]U8[/C][C]0.447[/C][C]0.383[/C][/ROW]
[ROW][C]U9[/C][C]0.453[/C][C]0.485[/C][/ROW]
[ROW][C]U10[/C][C]0.398[/C][C]-0.002[/C][/ROW]
[ROW][C]U11[/C][C]0.375[/C][C]0.273[/C][/ROW]
[ROW][C]U12[/C][C]0.559[/C][C]0.098[/C][/ROW]
[ROW][C]U13[/C][C]0.61[/C][C]0.215[/C][/ROW]
[ROW][C]U14[/C][C]0.486[/C][C]0.258[/C][/ROW]
[ROW][C]U15[/C][C]0.56[/C][C]0.314[/C][/ROW]
[ROW][C]U16[/C][C]0.646[/C][C]0.173[/C][/ROW]
[ROW][C]U17[/C][C]0.6[/C][C]0.178[/C][/ROW]
[ROW][C]U18[/C][C]0.624[/C][C]0.24[/C][/ROW]
[ROW][C]U19[/C][C]0.52[/C][C]0.305[/C][/ROW]
[ROW][C]U20[/C][C]0.709[/C][C]0.467[/C][/ROW]
[ROW][C]U21[/C][C]0.166[/C][C]0.809[/C][/ROW]
[ROW][C]U22[/C][C]0.221[/C][C]0.815[/C][/ROW]
[ROW][C]U23[/C][C]0.196[/C][C]0.767[/C][/ROW]
[ROW][C]U24[/C][C]0.236[/C][C]0.744[/C][/ROW]
[ROW][C]U25[/C][C]-0.449[/C][C]-0.455[/C][/ROW]
[ROW][C]U26[/C][C]0.322[/C][C]0.11[/C][/ROW]
[ROW][C]U27[/C][C]0.377[/C][C]0.325[/C][/ROW]
[ROW][C]U28[/C][C]0.135[/C][C]0.772[/C][/ROW]
[ROW][C]U29[/C][C]0.256[/C][C]0.731[/C][/ROW]
[ROW][C]U30[/C][C]0.514[/C][C]0.538[/C][/ROW]
[ROW][C]U31[/C][C]0.547[/C][C]0.459[/C][/ROW]
[ROW][C]U32[/C][C]0.53[/C][C]0.101[/C][/ROW]
[ROW][C]U33[/C][C]0.393[/C][C]0.115[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169563&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169563&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
U10.6790.466
U20.6650.467
U30.6490.369
U40.5350.486
U50.5890.405
U60.6170.405
U70.5850.471
U80.4470.383
U90.4530.485
U100.398-0.002
U110.3750.273
U120.5590.098
U130.610.215
U140.4860.258
U150.560.314
U160.6460.173
U170.60.178
U180.6240.24
U190.520.305
U200.7090.467
U210.1660.809
U220.2210.815
U230.1960.767
U240.2360.744
U25-0.449-0.455
U260.3220.11
U270.3770.325
U280.1350.772
U290.2560.731
U300.5140.538
U310.5470.459
U320.530.101
U330.3930.115


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = all ; par3 = all ; par4 = all ; par5 = CSUQ ;
Parameters (R input):
par1 = 2 ; par2 = all ; par3 = all ; 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')