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 computationSun, 29 Apr 2012 07:46:45 -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/29/t133570001718xc10lhebdukjx.htm/, Retrieved Sat, 04 May 2024 18:40:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165135, Retrieved Sat, 04 May 2024 18:40:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138

Tree of Dependent Computations

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] [729e3e98c2c68b03161978d53cee5b12]
-   P     [Factor Analysis] [] [2012-04-29 11:46:45] [685fae5a377cc1dc51f9f02306b751ce] [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 time2 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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165135&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]2 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=165135&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165135&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Rotated Factor Loadings
VariablesFactor1Factor2
U10.6460.501
U20.650.49
U30.6380.414
U40.5040.524
U50.5560.435
U60.5820.457
U70.6010.481
U80.5370.346
U90.4560.495
U100.3440.105
U110.4090.298
U120.5040.3
U130.4980.388
U140.40.399
U150.4340.453
U160.6220.241
U170.6260.189
U180.6990.212
U190.5330.338
U200.6990.514
U210.1480.848
U220.2420.847
U230.2080.736
U240.2110.747
U25-0.479-0.437
U260.4010.028
U270.4890.249
U280.1560.792
U290.2890.752
U300.4970.597
U310.5980.473
U320.6140.104
U330.4940.057

\begin{tabular}{lllllllll}
\hline
Rotated Factor Loadings \tabularnewline
Variables & Factor1 & Factor2 \tabularnewline
U1 & 0.646 & 0.501 \tabularnewline
U2 & 0.65 & 0.49 \tabularnewline
U3 & 0.638 & 0.414 \tabularnewline
U4 & 0.504 & 0.524 \tabularnewline
U5 & 0.556 & 0.435 \tabularnewline
U6 & 0.582 & 0.457 \tabularnewline
U7 & 0.601 & 0.481 \tabularnewline
U8 & 0.537 & 0.346 \tabularnewline
U9 & 0.456 & 0.495 \tabularnewline
U10 & 0.344 & 0.105 \tabularnewline
U11 & 0.409 & 0.298 \tabularnewline
U12 & 0.504 & 0.3 \tabularnewline
U13 & 0.498 & 0.388 \tabularnewline
U14 & 0.4 & 0.399 \tabularnewline
U15 & 0.434 & 0.453 \tabularnewline
U16 & 0.622 & 0.241 \tabularnewline
U17 & 0.626 & 0.189 \tabularnewline
U18 & 0.699 & 0.212 \tabularnewline
U19 & 0.533 & 0.338 \tabularnewline
U20 & 0.699 & 0.514 \tabularnewline
U21 & 0.148 & 0.848 \tabularnewline
U22 & 0.242 & 0.847 \tabularnewline
U23 & 0.208 & 0.736 \tabularnewline
U24 & 0.211 & 0.747 \tabularnewline
U25 & -0.479 & -0.437 \tabularnewline
U26 & 0.401 & 0.028 \tabularnewline
U27 & 0.489 & 0.249 \tabularnewline
U28 & 0.156 & 0.792 \tabularnewline
U29 & 0.289 & 0.752 \tabularnewline
U30 & 0.497 & 0.597 \tabularnewline
U31 & 0.598 & 0.473 \tabularnewline
U32 & 0.614 & 0.104 \tabularnewline
U33 & 0.494 & 0.057 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165135&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]0.646[/C][C]0.501[/C][/ROW]
[ROW][C]U2[/C][C]0.65[/C][C]0.49[/C][/ROW]
[ROW][C]U3[/C][C]0.638[/C][C]0.414[/C][/ROW]
[ROW][C]U4[/C][C]0.504[/C][C]0.524[/C][/ROW]
[ROW][C]U5[/C][C]0.556[/C][C]0.435[/C][/ROW]
[ROW][C]U6[/C][C]0.582[/C][C]0.457[/C][/ROW]
[ROW][C]U7[/C][C]0.601[/C][C]0.481[/C][/ROW]
[ROW][C]U8[/C][C]0.537[/C][C]0.346[/C][/ROW]
[ROW][C]U9[/C][C]0.456[/C][C]0.495[/C][/ROW]
[ROW][C]U10[/C][C]0.344[/C][C]0.105[/C][/ROW]
[ROW][C]U11[/C][C]0.409[/C][C]0.298[/C][/ROW]
[ROW][C]U12[/C][C]0.504[/C][C]0.3[/C][/ROW]
[ROW][C]U13[/C][C]0.498[/C][C]0.388[/C][/ROW]
[ROW][C]U14[/C][C]0.4[/C][C]0.399[/C][/ROW]
[ROW][C]U15[/C][C]0.434[/C][C]0.453[/C][/ROW]
[ROW][C]U16[/C][C]0.622[/C][C]0.241[/C][/ROW]
[ROW][C]U17[/C][C]0.626[/C][C]0.189[/C][/ROW]
[ROW][C]U18[/C][C]0.699[/C][C]0.212[/C][/ROW]
[ROW][C]U19[/C][C]0.533[/C][C]0.338[/C][/ROW]
[ROW][C]U20[/C][C]0.699[/C][C]0.514[/C][/ROW]
[ROW][C]U21[/C][C]0.148[/C][C]0.848[/C][/ROW]
[ROW][C]U22[/C][C]0.242[/C][C]0.847[/C][/ROW]
[ROW][C]U23[/C][C]0.208[/C][C]0.736[/C][/ROW]
[ROW][C]U24[/C][C]0.211[/C][C]0.747[/C][/ROW]
[ROW][C]U25[/C][C]-0.479[/C][C]-0.437[/C][/ROW]
[ROW][C]U26[/C][C]0.401[/C][C]0.028[/C][/ROW]
[ROW][C]U27[/C][C]0.489[/C][C]0.249[/C][/ROW]
[ROW][C]U28[/C][C]0.156[/C][C]0.792[/C][/ROW]
[ROW][C]U29[/C][C]0.289[/C][C]0.752[/C][/ROW]
[ROW][C]U30[/C][C]0.497[/C][C]0.597[/C][/ROW]
[ROW][C]U31[/C][C]0.598[/C][C]0.473[/C][/ROW]
[ROW][C]U32[/C][C]0.614[/C][C]0.104[/C][/ROW]
[ROW][C]U33[/C][C]0.494[/C][C]0.057[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165135&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165135&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
U10.6460.501
U20.650.49
U30.6380.414
U40.5040.524
U50.5560.435
U60.5820.457
U70.6010.481
U80.5370.346
U90.4560.495
U100.3440.105
U110.4090.298
U120.5040.3
U130.4980.388
U140.40.399
U150.4340.453
U160.6220.241
U170.6260.189
U180.6990.212
U190.5330.338
U200.6990.514
U210.1480.848
U220.2420.847
U230.2080.736
U240.2110.747
U25-0.479-0.437
U260.4010.028
U270.4890.249
U280.1560.792
U290.2890.752
U300.4970.597
U310.5980.473
U320.6140.104
U330.4940.057


Figures (Output of Computation)

Input Parameters & R Code

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