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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 computationMon, 30 Apr 2012 09:13:04 -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/Apr/30/t1335791611c1zjubqyh6ifzlr.htm/, Retrieved Sun, 28 Apr 2024 23:37:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165252, Retrieved Sun, 28 Apr 2024 23:37:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [FemaleBa2] [2012-04-30 13:13:04] [050dc696fa22882d0c3b1ebe5a70a85e] [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 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=165252&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=165252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165252&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Rotated Factor Loadings
VariablesFactor1Factor2
A10.481-0.019
A2-0.1430.579
A30.5650.013
A40.2450.498
A50.3080.244
A60.4730.157
A70.0510.446
A80.5140.353
A90.030.54
A100.4890.14
A110.461-0.609
A120.2010.472
A130.1660.356
A140.3230.474
A150.644-0.222
A160.458-0.432
A170.4370.145
A180.521-0.008
A190.5850.146
A200.2990.113

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
A1 & 0.481 & -0.019 \tabularnewline
A2 & -0.143 & 0.579 \tabularnewline
A3 & 0.565 & 0.013 \tabularnewline
A4 & 0.245 & 0.498 \tabularnewline
A5 & 0.308 & 0.244 \tabularnewline
A6 & 0.473 & 0.157 \tabularnewline
A7 & 0.051 & 0.446 \tabularnewline
A8 & 0.514 & 0.353 \tabularnewline
A9 & 0.03 & 0.54 \tabularnewline
A10 & 0.489 & 0.14 \tabularnewline
A11 & 0.461 & -0.609 \tabularnewline
A12 & 0.201 & 0.472 \tabularnewline
A13 & 0.166 & 0.356 \tabularnewline
A14 & 0.323 & 0.474 \tabularnewline
A15 & 0.644 & -0.222 \tabularnewline
A16 & 0.458 & -0.432 \tabularnewline
A17 & 0.437 & 0.145 \tabularnewline
A18 & 0.521 & -0.008 \tabularnewline
A19 & 0.585 & 0.146 \tabularnewline
A20 & 0.299 & 0.113 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165252&T=1

[TABLE]
[ROW][C]Rotated Factor Loadings[/C][/ROW]
[ROW][C]Variables[/C][C]Factor1[/C][C]Factor2[/C][/ROW]
[ROW][C]A1[/C][C]0.481[/C][C]-0.019[/C][/ROW]
[ROW][C]A2[/C][C]-0.143[/C][C]0.579[/C][/ROW]
[ROW][C]A3[/C][C]0.565[/C][C]0.013[/C][/ROW]
[ROW][C]A4[/C][C]0.245[/C][C]0.498[/C][/ROW]
[ROW][C]A5[/C][C]0.308[/C][C]0.244[/C][/ROW]
[ROW][C]A6[/C][C]0.473[/C][C]0.157[/C][/ROW]
[ROW][C]A7[/C][C]0.051[/C][C]0.446[/C][/ROW]
[ROW][C]A8[/C][C]0.514[/C][C]0.353[/C][/ROW]
[ROW][C]A9[/C][C]0.03[/C][C]0.54[/C][/ROW]
[ROW][C]A10[/C][C]0.489[/C][C]0.14[/C][/ROW]
[ROW][C]A11[/C][C]0.461[/C][C]-0.609[/C][/ROW]
[ROW][C]A12[/C][C]0.201[/C][C]0.472[/C][/ROW]
[ROW][C]A13[/C][C]0.166[/C][C]0.356[/C][/ROW]
[ROW][C]A14[/C][C]0.323[/C][C]0.474[/C][/ROW]
[ROW][C]A15[/C][C]0.644[/C][C]-0.222[/C][/ROW]
[ROW][C]A16[/C][C]0.458[/C][C]-0.432[/C][/ROW]
[ROW][C]A17[/C][C]0.437[/C][C]0.145[/C][/ROW]
[ROW][C]A18[/C][C]0.521[/C][C]-0.008[/C][/ROW]
[ROW][C]A19[/C][C]0.585[/C][C]0.146[/C][/ROW]
[ROW][C]A20[/C][C]0.299[/C][C]0.113[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165252&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
A10.481-0.019
A2-0.1430.579
A30.5650.013
A40.2450.498
A50.3080.244
A60.4730.157
A70.0510.446
A80.5140.353
A90.030.54
A100.4890.14
A110.461-0.609
A120.2010.472
A130.1660.356
A140.3230.474
A150.644-0.222
A160.458-0.432
A170.4370.145
A180.521-0.008
A190.5850.146
A200.2990.113


Figures (Output of Computation)

Input Parameters & R Code

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