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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 computationThu, 24 May 2012 16:45:01 -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/24/t1337892321xm1xghjpoh3b72s.htm/, Retrieved Sun, 05 May 2024 11:59:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167411, Retrieved Sun, 05 May 2024 11:59:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [fa] [2012-05-24 20:45:01] [935c692b8d0e827208dbfd6a4efb0528] [Current]
- RMP     [Data Mining] [corr] [2012-05-24 20:56:48] [7e17e0c557325a60eb6c8af681a1c273]
- RMP     [Hierarchical Clustering] [hc] [2012-05-24 21:47:45] [7e17e0c557325a60eb6c8af681a1c273]
- RMP     [Data Mining] [ma] [2012-05-24 22:30:18] [7e17e0c557325a60eb6c8af681a1c273]
-   P     [Factor Analysis] [faa] [2012-05-24 22:53:09] [7e17e0c557325a60eb6c8af681a1c273]
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Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167411&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167411&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167411&T=0

As an alternative you can also use a 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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Rotated Factor Loadings
VariablesFactor1Factor2
X10.2610.261
X20.1440.348
X30.230.185
X40.4560.061
X50.050.366
X60.596-0.177
X70.1470.567
X80.5820.022
X90.377-0.005
X100.4740.133
X11-0.1910.441
X12-0.0090.338
X130.0070.389
X14-0.0730.491
X15-0.0880.233
X160.215-0.017
X170.210.274
X180.515-0.068

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
X1 & 0.261 & 0.261 \tabularnewline
X2 & 0.144 & 0.348 \tabularnewline
X3 & 0.23 & 0.185 \tabularnewline
X4 & 0.456 & 0.061 \tabularnewline
X5 & 0.05 & 0.366 \tabularnewline
X6 & 0.596 & -0.177 \tabularnewline
X7 & 0.147 & 0.567 \tabularnewline
X8 & 0.582 & 0.022 \tabularnewline
X9 & 0.377 & -0.005 \tabularnewline
X10 & 0.474 & 0.133 \tabularnewline
X11 & -0.191 & 0.441 \tabularnewline
X12 & -0.009 & 0.338 \tabularnewline
X13 & 0.007 & 0.389 \tabularnewline
X14 & -0.073 & 0.491 \tabularnewline
X15 & -0.088 & 0.233 \tabularnewline
X16 & 0.215 & -0.017 \tabularnewline
X17 & 0.21 & 0.274 \tabularnewline
X18 & 0.515 & -0.068 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167411&T=1

[TABLE]
[ROW][C]Rotated Factor Loadings[/C][/ROW]
[ROW][C]Variables[/C][C]Factor1[/C][C]Factor2[/C][/ROW]
[ROW][C]X1[/C][C]0.261[/C][C]0.261[/C][/ROW]
[ROW][C]X2[/C][C]0.144[/C][C]0.348[/C][/ROW]
[ROW][C]X3[/C][C]0.23[/C][C]0.185[/C][/ROW]
[ROW][C]X4[/C][C]0.456[/C][C]0.061[/C][/ROW]
[ROW][C]X5[/C][C]0.05[/C][C]0.366[/C][/ROW]
[ROW][C]X6[/C][C]0.596[/C][C]-0.177[/C][/ROW]
[ROW][C]X7[/C][C]0.147[/C][C]0.567[/C][/ROW]
[ROW][C]X8[/C][C]0.582[/C][C]0.022[/C][/ROW]
[ROW][C]X9[/C][C]0.377[/C][C]-0.005[/C][/ROW]
[ROW][C]X10[/C][C]0.474[/C][C]0.133[/C][/ROW]
[ROW][C]X11[/C][C]-0.191[/C][C]0.441[/C][/ROW]
[ROW][C]X12[/C][C]-0.009[/C][C]0.338[/C][/ROW]
[ROW][C]X13[/C][C]0.007[/C][C]0.389[/C][/ROW]
[ROW][C]X14[/C][C]-0.073[/C][C]0.491[/C][/ROW]
[ROW][C]X15[/C][C]-0.088[/C][C]0.233[/C][/ROW]
[ROW][C]X16[/C][C]0.215[/C][C]-0.017[/C][/ROW]
[ROW][C]X17[/C][C]0.21[/C][C]0.274[/C][/ROW]
[ROW][C]X18[/C][C]0.515[/C][C]-0.068[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167411&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167411&T=1

As an alternative you can also use a QR Code:  

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

Rotated Factor Loadings
VariablesFactor1Factor2
X10.2610.261
X20.1440.348
X30.230.185
X40.4560.061
X50.050.366
X60.596-0.177
X70.1470.567
X80.5820.022
X90.377-0.005
X100.4740.133
X11-0.1910.441
X12-0.0090.338
X130.0070.389
X14-0.0730.491
X15-0.0880.233
X160.215-0.017
X170.210.274
X180.515-0.068



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