Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_factor_analysisdm.wasp

Title produced by software

Factor Analysis

Date of computation

Thu, 26 Apr 2012 09:01:12 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/26/t1335445281mlbi4bssuq4i9ut.htm/, Retrieved Sun, 15 Feb 2026 04:33:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164900, Retrieved Sun, 15 Feb 2026 04:33:52 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

333

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Factor Analysis] [] [2012-04-26 13:01:12] [685fae5a377cc1dc51f9f02306b751ce] [Current]
- R P     [Factor Analysis] [] [2012-04-29 11:46:12] [729e3e98c2c68b03161978d53cee5b12] 
-   P     [Factor Analysis] [] [2012-04-29 11:46:45] [729e3e98c2c68b03161978d53cee5b12] 
- RMP     [Data Mining] [] [2012-04-29 11:48:32] [729e3e98c2c68b03161978d53cee5b12] 
- RMP     [Data Mining] [] [2012-04-29 12:21:33] [729e3e98c2c68b03161978d53cee5b12] 
- R P       [Data Mining] [] [2012-05-21 14:03:21] [74be16979710d4c4e7c6647856088456] 
- RMP     [Data Mining] [] [2012-04-29 12:24:46] [729e3e98c2c68b03161978d53cee5b12] 
- RMP     [Data Mining] [] [2012-04-29 12:26:36] [729e3e98c2c68b03161978d53cee5b12] 
-           [Data Mining] [] [2012-04-29 12:32:23] [729e3e98c2c68b03161978d53cee5b12] 
-           [Data Mining] [] [2012-04-29 13:16:14] [729e3e98c2c68b03161978d53cee5b12] 
- R P         [Data Mining] [] [2012-05-21 14:01:01] [74be16979710d4c4e7c6647856088456] 
-           [Data Mining] [] [2012-04-29 13:39:17] [729e3e98c2c68b03161978d53cee5b12] 
- R P         [Data Mining] [] [2012-05-21 14:12:12] [74be16979710d4c4e7c6647856088456] 

Feedback Forum

Post a new message

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164900&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164900&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164900&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Rotated Factor Loadings
Variables	Factor1	Factor2
A1	0.575	-0.024
A2	-0.109	0.443
A3	0.443	0.285
A4	-0.057	0.506
A5	0.171	0.455
A6	0.418	0.409
A7	0.321	0.381
A8	0.341	0.526
A9	0.184	0.4
A10	0.493	0.149
A11	0.523	-0.367
A12	0.128	0.547
A13	-0.108	0.536
A14	0.282	0.361
A15	0.499	0.205
A16	0.592	-0.226
A17	0.457	0.106
A18	0.392	0.185
A19	0.232	0.476
A20	0.483	0.086

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
A1 & 0.575 & -0.024 \tabularnewline
A2 & -0.109 & 0.443 \tabularnewline
A3 & 0.443 & 0.285 \tabularnewline
A4 & -0.057 & 0.506 \tabularnewline
A5 & 0.171 & 0.455 \tabularnewline
A6 & 0.418 & 0.409 \tabularnewline
A7 & 0.321 & 0.381 \tabularnewline
A8 & 0.341 & 0.526 \tabularnewline
A9 & 0.184 & 0.4 \tabularnewline
A10 & 0.493 & 0.149 \tabularnewline
A11 & 0.523 & -0.367 \tabularnewline
A12 & 0.128 & 0.547 \tabularnewline
A13 & -0.108 & 0.536 \tabularnewline
A14 & 0.282 & 0.361 \tabularnewline
A15 & 0.499 & 0.205 \tabularnewline
A16 & 0.592 & -0.226 \tabularnewline
A17 & 0.457 & 0.106 \tabularnewline
A18 & 0.392 & 0.185 \tabularnewline
A19 & 0.232 & 0.476 \tabularnewline
A20 & 0.483 & 0.086 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164900&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]0.575[/C][C]-0.024[/C][/ROW]
[ROW][C]A2[/C][C]-0.109[/C][C]0.443[/C][/ROW]
[ROW][C]A3[/C][C]0.443[/C][C]0.285[/C][/ROW]
[ROW][C]A4[/C][C]-0.057[/C][C]0.506[/C][/ROW]
[ROW][C]A5[/C][C]0.171[/C][C]0.455[/C][/ROW]
[ROW][C]A6[/C][C]0.418[/C][C]0.409[/C][/ROW]
[ROW][C]A7[/C][C]0.321[/C][C]0.381[/C][/ROW]
[ROW][C]A8[/C][C]0.341[/C][C]0.526[/C][/ROW]
[ROW][C]A9[/C][C]0.184[/C][C]0.4[/C][/ROW]
[ROW][C]A10[/C][C]0.493[/C][C]0.149[/C][/ROW]
[ROW][C]A11[/C][C]0.523[/C][C]-0.367[/C][/ROW]
[ROW][C]A12[/C][C]0.128[/C][C]0.547[/C][/ROW]
[ROW][C]A13[/C][C]-0.108[/C][C]0.536[/C][/ROW]
[ROW][C]A14[/C][C]0.282[/C][C]0.361[/C][/ROW]
[ROW][C]A15[/C][C]0.499[/C][C]0.205[/C][/ROW]
[ROW][C]A16[/C][C]0.592[/C][C]-0.226[/C][/ROW]
[ROW][C]A17[/C][C]0.457[/C][C]0.106[/C][/ROW]
[ROW][C]A18[/C][C]0.392[/C][C]0.185[/C][/ROW]
[ROW][C]A19[/C][C]0.232[/C][C]0.476[/C][/ROW]
[ROW][C]A20[/C][C]0.483[/C][C]0.086[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164900&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164900&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
Variables	Factor1	Factor2
A1	0.575	-0.024
A2	-0.109	0.443
A3	0.443	0.285
A4	-0.057	0.506
A5	0.171	0.455
A6	0.418	0.409
A7	0.321	0.381
A8	0.341	0.526
A9	0.184	0.4
A10	0.493	0.149
A11	0.523	-0.367
A12	0.128	0.547
A13	-0.108	0.536
A14	0.282	0.361
A15	0.499	0.205
A16	0.592	-0.226
A17	0.457	0.106
A18	0.392	0.185
A19	0.232	0.476
A20	0.483	0.086

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = male ; par3 = all ; par4 = all ; par5 = ATTLES all ;

Parameters (R input):

par1 = 2 ; par2 = male ; par3 = all ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code