FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 10:34:34 -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/t1335882886yfqhf4lo72d17ev.htm/, Retrieved Sat, 04 May 2024 17:26:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165621, Retrieved Sat, 04 May 2024 17:26:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Factor Analysis] [male-prep] [2012-05-01 14:34:34] [c38c32477296496b546025b407c5c736] [Current]
Feedback Forum

Post a new message

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=165621&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=165621&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165621&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
U10.6430.491
U20.6420.502
U30.6840.355
U40.5870.474
U50.5580.378
U60.6320.362
U70.6120.499
U80.5240.398
U90.4290.501
U100.3130.159
U110.4360.286
U120.5490.239
U130.4960.347
U140.50.303
U150.4710.399
U160.5810.181
U170.630.225
U180.6920.226
U190.5450.298
U200.6870.517
U210.1360.809
U220.1990.863
U230.2170.747
U240.1280.733
U25-0.402-0.549
U260.369-0.034
U270.4150.359
U280.1040.747
U290.3030.793
U300.4930.598
U310.5350.532
U320.6470.079
U330.424-0.018

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
U1 & 0.643 & 0.491 \tabularnewline
U2 & 0.642 & 0.502 \tabularnewline
U3 & 0.684 & 0.355 \tabularnewline
U4 & 0.587 & 0.474 \tabularnewline
U5 & 0.558 & 0.378 \tabularnewline
U6 & 0.632 & 0.362 \tabularnewline
U7 & 0.612 & 0.499 \tabularnewline
U8 & 0.524 & 0.398 \tabularnewline
U9 & 0.429 & 0.501 \tabularnewline
U10 & 0.313 & 0.159 \tabularnewline
U11 & 0.436 & 0.286 \tabularnewline
U12 & 0.549 & 0.239 \tabularnewline
U13 & 0.496 & 0.347 \tabularnewline
U14 & 0.5 & 0.303 \tabularnewline
U15 & 0.471 & 0.399 \tabularnewline
U16 & 0.581 & 0.181 \tabularnewline
U17 & 0.63 & 0.225 \tabularnewline
U18 & 0.692 & 0.226 \tabularnewline
U19 & 0.545 & 0.298 \tabularnewline
U20 & 0.687 & 0.517 \tabularnewline
U21 & 0.136 & 0.809 \tabularnewline
U22 & 0.199 & 0.863 \tabularnewline
U23 & 0.217 & 0.747 \tabularnewline
U24 & 0.128 & 0.733 \tabularnewline
U25 & -0.402 & -0.549 \tabularnewline
U26 & 0.369 & -0.034 \tabularnewline
U27 & 0.415 & 0.359 \tabularnewline
U28 & 0.104 & 0.747 \tabularnewline
U29 & 0.303 & 0.793 \tabularnewline
U30 & 0.493 & 0.598 \tabularnewline
U31 & 0.535 & 0.532 \tabularnewline
U32 & 0.647 & 0.079 \tabularnewline
U33 & 0.424 & -0.018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165621&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]0.643[/C][C]0.491[/C][/ROW]
[ROW][C]U2[/C][C]0.642[/C][C]0.502[/C][/ROW]
[ROW][C]U3[/C][C]0.684[/C][C]0.355[/C][/ROW]
[ROW][C]U4[/C][C]0.587[/C][C]0.474[/C][/ROW]
[ROW][C]U5[/C][C]0.558[/C][C]0.378[/C][/ROW]
[ROW][C]U6[/C][C]0.632[/C][C]0.362[/C][/ROW]
[ROW][C]U7[/C][C]0.612[/C][C]0.499[/C][/ROW]
[ROW][C]U8[/C][C]0.524[/C][C]0.398[/C][/ROW]
[ROW][C]U9[/C][C]0.429[/C][C]0.501[/C][/ROW]
[ROW][C]U10[/C][C]0.313[/C][C]0.159[/C][/ROW]
[ROW][C]U11[/C][C]0.436[/C][C]0.286[/C][/ROW]
[ROW][C]U12[/C][C]0.549[/C][C]0.239[/C][/ROW]
[ROW][C]U13[/C][C]0.496[/C][C]0.347[/C][/ROW]
[ROW][C]U14[/C][C]0.5[/C][C]0.303[/C][/ROW]
[ROW][C]U15[/C][C]0.471[/C][C]0.399[/C][/ROW]
[ROW][C]U16[/C][C]0.581[/C][C]0.181[/C][/ROW]
[ROW][C]U17[/C][C]0.63[/C][C]0.225[/C][/ROW]
[ROW][C]U18[/C][C]0.692[/C][C]0.226[/C][/ROW]
[ROW][C]U19[/C][C]0.545[/C][C]0.298[/C][/ROW]
[ROW][C]U20[/C][C]0.687[/C][C]0.517[/C][/ROW]
[ROW][C]U21[/C][C]0.136[/C][C]0.809[/C][/ROW]
[ROW][C]U22[/C][C]0.199[/C][C]0.863[/C][/ROW]
[ROW][C]U23[/C][C]0.217[/C][C]0.747[/C][/ROW]
[ROW][C]U24[/C][C]0.128[/C][C]0.733[/C][/ROW]
[ROW][C]U25[/C][C]-0.402[/C][C]-0.549[/C][/ROW]
[ROW][C]U26[/C][C]0.369[/C][C]-0.034[/C][/ROW]
[ROW][C]U27[/C][C]0.415[/C][C]0.359[/C][/ROW]
[ROW][C]U28[/C][C]0.104[/C][C]0.747[/C][/ROW]
[ROW][C]U29[/C][C]0.303[/C][C]0.793[/C][/ROW]
[ROW][C]U30[/C][C]0.493[/C][C]0.598[/C][/ROW]
[ROW][C]U31[/C][C]0.535[/C][C]0.532[/C][/ROW]
[ROW][C]U32[/C][C]0.647[/C][C]0.079[/C][/ROW]
[ROW][C]U33[/C][C]0.424[/C][C]-0.018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165621&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165621&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
U10.6430.491
U20.6420.502
U30.6840.355
U40.5870.474
U50.5580.378
U60.6320.362
U70.6120.499
U80.5240.398
U90.4290.501
U100.3130.159
U110.4360.286
U120.5490.239
U130.4960.347
U140.50.303
U150.4710.399
U160.5810.181
U170.630.225
U180.6920.226
U190.5450.298
U200.6870.517
U210.1360.809
U220.1990.863
U230.2170.747
U240.1280.733
U25-0.402-0.549
U260.369-0.034
U270.4150.359
U280.1040.747
U290.3030.793
U300.4930.598
U310.5350.532
U320.6470.079
U330.424-0.018


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 = male ; par3 = prep ; 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')