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Author's title

Author

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R Software Module

rwasp_factor_analysisdm.wasp

Title produced by software

Factor Analysis

Date of computation

Thu, 24 May 2012 05:48:27 -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/May/24/t1337852923p0lqhfdmvwfybb9.htm/, Retrieved Sun, 05 May 2024 22:42:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167276, Retrieved Sun, 05 May 2024 22:42:29 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

133

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

-     [Hierarchical Clustering] [] [2012-04-22 11:59:33] [182e2e10fa38557ff81755a04c8c64c0]
- RMPD    [Factor Analysis] [] [2012-05-24 09:48:27] [aedc5b8e4f26bdca34b1a0cf88d6dfa2] [Current]
-           [Factor Analysis] [] [2012-05-24 09:49:40] [2805bc4d0d3810b6cd96238758e5985d] 
-           [Factor Analysis] [] [2012-05-24 09:53:47] [2805bc4d0d3810b6cd96238758e5985d] 
-           [Factor Analysis] [] [2012-05-24 10:02:20] [2805bc4d0d3810b6cd96238758e5985d] 
-           [Factor Analysis] [] [2012-05-24 10:02:51] [2805bc4d0d3810b6cd96238758e5985d] 
- RM        [Social Networking] [] [2012-05-24 10:10:03] [2805bc4d0d3810b6cd96238758e5985d] 
-             [Social Networking] [] [2012-05-24 10:11:34] [2805bc4d0d3810b6cd96238758e5985d] 
- RM          [Social Networking] [] [2012-05-24 10:18:52] [2805bc4d0d3810b6cd96238758e5985d] 
- RM          [Data Mining] [] [2012-05-24 13:32:03] [2805bc4d0d3810b6cd96238758e5985d] 
- RM          [Data Mining] [] [2012-05-24 13:41:22] [2805bc4d0d3810b6cd96238758e5985d] 
-               [Data Mining] [] [2012-05-24 13:43:27] [2805bc4d0d3810b6cd96238758e5985d] 
-               [Data Mining] [] [2012-05-24 13:47:58] [2805bc4d0d3810b6cd96238758e5985d] 
-               [Data Mining] [] [2012-05-24 13:49:40] [2805bc4d0d3810b6cd96238758e5985d] 

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'AstonUniversity' @ aston.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 & 3 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167276&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167276&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167276&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	3 seconds
R Server	'AstonUniversity' @ aston.wessa.net

Rotated Factor Loadings
Variables	Factor1	Factor2
U1	0.672	0.477
U2	0.666	0.49
U3	0.674	0.396
U4	0.607	0.444
U5	0.566	0.439
U6	0.646	0.368
U7	0.576	0.503
U8	0.449	0.443
U9	0.418	0.531
U10	0.31	0.144
U11	0.358	0.363
U12	0.57	0.124
U13	0.581	0.26
U14	0.528	0.269
U15	0.573	0.349
U16	0.661	0.148
U17	0.624	0.179
U18	0.635	0.228
U19	0.521	0.285
U20	0.716	0.475
U21	0.175	0.779
U22	0.232	0.819
U23	0.199	0.788
U24	0.173	0.756
U25	-0.38	-0.529
U26	0.317	0.062
U27	0.386	0.314
U28	0.115	0.731
U29	0.241	0.788
U30	0.493	0.586
U31	0.534	0.515
U32	0.574	0.092
U33	0.415	0.032

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
U1 & 0.672 & 0.477 \tabularnewline
U2 & 0.666 & 0.49 \tabularnewline
U3 & 0.674 & 0.396 \tabularnewline
U4 & 0.607 & 0.444 \tabularnewline
U5 & 0.566 & 0.439 \tabularnewline
U6 & 0.646 & 0.368 \tabularnewline
U7 & 0.576 & 0.503 \tabularnewline
U8 & 0.449 & 0.443 \tabularnewline
U9 & 0.418 & 0.531 \tabularnewline
U10 & 0.31 & 0.144 \tabularnewline
U11 & 0.358 & 0.363 \tabularnewline
U12 & 0.57 & 0.124 \tabularnewline
U13 & 0.581 & 0.26 \tabularnewline
U14 & 0.528 & 0.269 \tabularnewline
U15 & 0.573 & 0.349 \tabularnewline
U16 & 0.661 & 0.148 \tabularnewline
U17 & 0.624 & 0.179 \tabularnewline
U18 & 0.635 & 0.228 \tabularnewline
U19 & 0.521 & 0.285 \tabularnewline
U20 & 0.716 & 0.475 \tabularnewline
U21 & 0.175 & 0.779 \tabularnewline
U22 & 0.232 & 0.819 \tabularnewline
U23 & 0.199 & 0.788 \tabularnewline
U24 & 0.173 & 0.756 \tabularnewline
U25 & -0.38 & -0.529 \tabularnewline
U26 & 0.317 & 0.062 \tabularnewline
U27 & 0.386 & 0.314 \tabularnewline
U28 & 0.115 & 0.731 \tabularnewline
U29 & 0.241 & 0.788 \tabularnewline
U30 & 0.493 & 0.586 \tabularnewline
U31 & 0.534 & 0.515 \tabularnewline
U32 & 0.574 & 0.092 \tabularnewline
U33 & 0.415 & 0.032 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167276&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]0.672[/C][C]0.477[/C][/ROW]
[ROW][C]U2[/C][C]0.666[/C][C]0.49[/C][/ROW]
[ROW][C]U3[/C][C]0.674[/C][C]0.396[/C][/ROW]
[ROW][C]U4[/C][C]0.607[/C][C]0.444[/C][/ROW]
[ROW][C]U5[/C][C]0.566[/C][C]0.439[/C][/ROW]
[ROW][C]U6[/C][C]0.646[/C][C]0.368[/C][/ROW]
[ROW][C]U7[/C][C]0.576[/C][C]0.503[/C][/ROW]
[ROW][C]U8[/C][C]0.449[/C][C]0.443[/C][/ROW]
[ROW][C]U9[/C][C]0.418[/C][C]0.531[/C][/ROW]
[ROW][C]U10[/C][C]0.31[/C][C]0.144[/C][/ROW]
[ROW][C]U11[/C][C]0.358[/C][C]0.363[/C][/ROW]
[ROW][C]U12[/C][C]0.57[/C][C]0.124[/C][/ROW]
[ROW][C]U13[/C][C]0.581[/C][C]0.26[/C][/ROW]
[ROW][C]U14[/C][C]0.528[/C][C]0.269[/C][/ROW]
[ROW][C]U15[/C][C]0.573[/C][C]0.349[/C][/ROW]
[ROW][C]U16[/C][C]0.661[/C][C]0.148[/C][/ROW]
[ROW][C]U17[/C][C]0.624[/C][C]0.179[/C][/ROW]
[ROW][C]U18[/C][C]0.635[/C][C]0.228[/C][/ROW]
[ROW][C]U19[/C][C]0.521[/C][C]0.285[/C][/ROW]
[ROW][C]U20[/C][C]0.716[/C][C]0.475[/C][/ROW]
[ROW][C]U21[/C][C]0.175[/C][C]0.779[/C][/ROW]
[ROW][C]U22[/C][C]0.232[/C][C]0.819[/C][/ROW]
[ROW][C]U23[/C][C]0.199[/C][C]0.788[/C][/ROW]
[ROW][C]U24[/C][C]0.173[/C][C]0.756[/C][/ROW]
[ROW][C]U25[/C][C]-0.38[/C][C]-0.529[/C][/ROW]
[ROW][C]U26[/C][C]0.317[/C][C]0.062[/C][/ROW]
[ROW][C]U27[/C][C]0.386[/C][C]0.314[/C][/ROW]
[ROW][C]U28[/C][C]0.115[/C][C]0.731[/C][/ROW]
[ROW][C]U29[/C][C]0.241[/C][C]0.788[/C][/ROW]
[ROW][C]U30[/C][C]0.493[/C][C]0.586[/C][/ROW]
[ROW][C]U31[/C][C]0.534[/C][C]0.515[/C][/ROW]
[ROW][C]U32[/C][C]0.574[/C][C]0.092[/C][/ROW]
[ROW][C]U33[/C][C]0.415[/C][C]0.032[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167276&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167276&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
U1	0.672	0.477
U2	0.666	0.49
U3	0.674	0.396
U4	0.607	0.444
U5	0.566	0.439
U6	0.646	0.368
U7	0.576	0.503
U8	0.449	0.443
U9	0.418	0.531
U10	0.31	0.144
U11	0.358	0.363
U12	0.57	0.124
U13	0.581	0.26
U14	0.528	0.269
U15	0.573	0.349
U16	0.661	0.148
U17	0.624	0.179
U18	0.635	0.228
U19	0.521	0.285
U20	0.716	0.475
U21	0.175	0.779
U22	0.232	0.819
U23	0.199	0.788
U24	0.173	0.756
U25	-0.38	-0.529
U26	0.317	0.062
U27	0.386	0.314
U28	0.115	0.731
U29	0.241	0.788
U30	0.493	0.586
U31	0.534	0.515
U32	0.574	0.092
U33	0.415	0.032

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 2 ; par2 = all ; par3 = prep ; par4 = all ; par5 = CSUQ ;

Parameters (R input):

par1 = 2 ; par2 = all ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code