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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationSun, 28 Nov 2010 11:12:07 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/28/t12909426298k4ao5b7vu6022p.htm/, Retrieved Thu, 02 May 2024 20:07:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=102483, Retrieved Thu, 02 May 2024 20:07:56 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cronbach Alpha] [Intrinsic Motivat...] [2010-10-12 11:42:57] [b98453cac15ba1066b407e146608df68]
- R  D  [Cronbach Alpha] [cronbach alpha P&...] [2010-11-27 09:41:56] [f730b099f190102bcd41f590a8dae16d]
- RMPD      [Survey Scores] [Popularity: quasi...] [2010-11-28 11:12:07] [350231caf55a86a218fd48dc4d2e2f8b] [Current]
-    D        [Survey Scores] [Paper: FindingFri...] [2010-11-28 11:37:20] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
-    D        [Survey Scores] [Paper: Knowing Qu...] [2010-11-28 12:08:09] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
-    D        [Survey Scores] [Paper: Liked Quas...] [2010-11-28 12:16:56] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
-   PD        [Survey Scores] [Paper: Popularity...] [2010-11-28 12:35:35] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
-   PD          [Survey Scores] [Paper: Popularity...] [2010-12-03 12:08:28] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
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Dataseries X:
3	3	3	-2
3	3	3	-3
4	4	4	-3
3	3	3	-3
3	2	2	-3
3	3	3	-3
3	4	4	-2
2	2	2	-3
3	3	3	-3
3	4	2	-4
3	3	2	-3
3	3	2	-3
3	4	4	-2
2	2	NA	-3
3	2	3	-3
3	3	2	-3
2	2	3	-3
3	4	4	-3
2	2	2	-2
1	1	2	-4
2	3	3	-3
3	4	4	-2
3	2	3	-3
3	3	3	-3
3	3	4	-2
3	4	4	-2
2	3	2	-4
3	3	3	-2
3	4	3	-3
4	4	4	-2
3	4	4	-4
3	3	3	-3
3	4	3	-2
3	3	2	-3
2	2	2	-3
3	4	4	-1
3	3	3	-3
3	2	2	-3
3	4	3	-3
4	4	4	-2
3	4	4	-3
3	4	2	NA
1	2	1	-5
2	2	2	-4
3	3	2	-3
4	4	4	-2
4	5	4	-2
2	2	2	-3
1	3	3	-4
3	3	3	-2
3	2	2	-3
1	2	1	-4
3	3	3	-3
2	2	2	-4
3	4	4	-3
3	3	3	-3
2	3	4	-4
4	4	4	-2
1	1	4	-4
3	4	4	-2
2	2	1	-4
4	4	4	-2
3	4	4	-3
4	4	4	-2
3	2	1	-3
3	4	4	-3
3	2	3	-3
3	4	3	-3
3	4	4	-2
1	1	1	-4
3	4	4	-2
3	4	3	-3
3	3	3	-4
2	3	2	-2
3	3	3	-3
3	3	3	-3
3	3	3	-3
2	3	4	-3
3	4	3	-2
2	1	1	-4
2	3	NA	-4
3	4	3	-2
3	3	4	-2
2	3	3	-4
2	4	4	-3
3	3	3	-3
2	2	2	-3
3	3	3	-3
4	4	4	-2
2	3	3	-4
3	4	4	-3
2	3	3	-4
4	4	4	-2
3	4	4	-2
3	3	3	-3
3	2	2	-3
3	1	1	-3
2	2	2	-4
3	2	2	-2
4	3	3	-3
4	4	4	-2
4	4	4	-2
3	3	5	-3
3	3	2	-3
1	1	1	-5
4	3	3	-2
1	3	3	-4
3	4	4	-3
2	2	2	-4
2	2	2	-4
3	3	2	-3
3	3	3	-3
2	3	3	-3
3	4	4	-3
3	4	4	-2
4	4	4	-2
4	4	4	-2
3	2	2	-2
3	3	3	-1
3	4	3	-2
3	3	3	-3
3	4	4	-3
1	2	3	-4
2	4	4	-3
4	4	4	-2
3	3	3	-3
4	4	4	-2
3	3	3	-3
2	3	3	-3
1	1	1	-5
4	4	4	-2
3	4	4	-2
3	2	2	-3
3	3	2	-1
4	4	4	-3
3	3	3	-3
3	4	4	-3
1	2	2	-4
4	5	5	-1
2	3	3	-2
2	4	4	-4
3	3	3	-2
3	4	4	-2
2	2	2	-4
3	3	3	-3
3	3	1	-3
2	2	2	-4
NA	NA	5	-1
3	4	4	-2
4	4	4	-2
4	3	3	-3
4	4	4	-2
2	2	2	-3
3	4	4	-3
3	4	4	-3
3	3	3	-3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102483&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102483&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102483&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
1-0.192454-0.382443-0.28
20.1162450.1660380.22
30.0460540.0557440.13
4-5.850907-10155-1

\begin{tabular}{lllllllll}
\hline
Summary of survey scores (median of Likert score was subtracted) \tabularnewline
Question & mean & Sum ofpositives (Ps) & Sum ofnegatives (Ns) & (Ps-Ns)/(Ps+Ns) & Count ofpositives (Pc) & Count ofnegatives (Nc) & (Pc-Nc)/(Pc+Nc) \tabularnewline
1 & -0.19 & 24 & 54 & -0.38 & 24 & 43 & -0.28 \tabularnewline
2 & 0.11 & 62 & 45 & 0.16 & 60 & 38 & 0.22 \tabularnewline
3 & 0.04 & 60 & 54 & 0.05 & 57 & 44 & 0.13 \tabularnewline
4 & -5.85 & 0 & 907 & -1 & 0 & 155 & -1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102483&T=1

[TABLE]
[ROW][C]Summary of survey scores (median of Likert score was subtracted)[/C][/ROW]
[ROW][C]Question[/C][C]mean[/C][C]Sum ofpositives (Ps)[/C][C]Sum ofnegatives (Ns)[/C][C](Ps-Ns)/(Ps+Ns)[/C][C]Count ofpositives (Pc)[/C][C]Count ofnegatives (Nc)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]1[/C][C]-0.19[/C][C]24[/C][C]54[/C][C]-0.38[/C][C]24[/C][C]43[/C][C]-0.28[/C][/ROW]
[ROW][C]2[/C][C]0.11[/C][C]62[/C][C]45[/C][C]0.16[/C][C]60[/C][C]38[/C][C]0.22[/C][/ROW]
[ROW][C]3[/C][C]0.04[/C][C]60[/C][C]54[/C][C]0.05[/C][C]57[/C][C]44[/C][C]0.13[/C][/ROW]
[ROW][C]4[/C][C]-5.85[/C][C]0[/C][C]907[/C][C]-1[/C][C]0[/C][C]155[/C][C]-1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102483&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102483&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
1-0.192454-0.382443-0.28
20.1162450.1660380.22
30.0460540.0557440.13
4-5.850907-10155-1







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.915 (0.085)0.936 (0.064)
(Ps-Ns)/(Ps+Ns)0.915 (0.085)1 (0)0.998 (0.002)
(Pc-Nc)/(Pc+Nc)0.936 (0.064)0.998 (0.002)1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.915 (0.085) & 0.936 (0.064) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.915 (0.085) & 1 (0) & 0.998 (0.002) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.936 (0.064) & 0.998 (0.002) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102483&T=2

[TABLE]
[ROW][C]Pearson correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.915 (0.085)[/C][C]0.936 (0.064)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.915 (0.085)[/C][C]1 (0)[/C][C]0.998 (0.002)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.936 (0.064)[/C][C]0.998 (0.002)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102483&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102483&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.915 (0.085)0.936 (0.064)
(Ps-Ns)/(Ps+Ns)0.915 (0.085)1 (0)0.998 (0.002)
(Pc-Nc)/(Pc+Nc)0.936 (0.064)0.998 (0.002)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0.083) & 1 (0.083) & 1 (0.083) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102483&T=3

[TABLE]
[ROW][C]Kendall tau rank correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][C]1 (0.083)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102483&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102483&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.083)1 (0.083)1 (0.083)
(Ps-Ns)/(Ps+Ns)1 (0.083)1 (0.083)1 (0.083)
(Pc-Nc)/(Pc+Nc)1 (0.083)1 (0.083)1 (0.083)



Parameters (Session):
par1 = 1 2 3 4 5 ;
Parameters (R input):
par1 = 1 2 3 4 5 ;
R code (references can be found in the software module):
docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')