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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 computationTue, 16 Dec 2014 10:22:39 +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/2014/Dec/16/t1418725409di0zi3497kz7rei.htm/, Retrieved Thu, 31 Oct 2024 23:54:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269254, Retrieved Thu, 31 Oct 2024 23:54:07 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataseries X:
1 1 1 1 4 2
2 1 2 4 3 3
2 2 2 4 4 2
2 4 4 4 4 4
3 2 2 2 1 2
3 3 3 2 2 2
3 2 2 4 4 2
3 2 3 4 4 4
3 1 3 2 2 2
2 2 3 2 3 3
3 1 3 1 4 2
2 2 2 1 2 1
2 2 2 2 4 2
2 2 2 1 2 2
2 2 4 4 4 2
2 3 0 1 2 4
3 4 3 4 4 3
2 2 2 2 4 1
4 2 3 3 2 1
3 2 2 3 4 4
1 2 4 3 4 4
1 2 2 2 4 2
2 2 2 2 3 3
3 4 4 3 5 5
3 3 3 4 4 4
3 3 4 4 4 4
2 2 2 2 4 2
2 2 2 2 4 2
1 2 2 2 3 1
1 1 1 1 1 1
2 3 2 2 4 2
1 3 3 4 2 4
2 2 2 2 4 2
2 3 3 1 3 4
2 2 2 4 4 4
2 2 4 2 4 2
3 4 4 1 4 2
3 2 3 2 2 4
3 3 2 2 4 3
3 4 4 3 4 2
2 1 1 1 2 1
4 2 2 2 2 2
3 3 2 3 2 4
2 1 1 1 2 1
2 2 3 2 4 4
2 2 2 2 4 4
2 2 2 2 3 2
2 2 2 1 2 2
5 5 5 5 5 5
3 4 4 2 4 5
3 2 4 1 3 4
2 4 4 2 3 2
1 1 1 1 3 1
2 2 2 3 3 2
3 1 1 2 2 4
4 4 4 4 3 3
4 2 4 1 4 1
2 2 1 1 3 1
2 2 2 2 3 2
2 2 4 2 4 3
2 2 2 2 4 2
2 1 3 3 4 4
5 3 4 3 4 5
2 2 2 1 2 2
2 2 3 2 3 4
2 1 1 1 4 1
2 2 2 2 2 3
2 3 3 4 4 4
1 2 4 2 1 1
1 1 1 1 1 1
2 2 2 4 4 4
2 2 2 2 3 2
2 2 2 2 3 2
4 4 3 3 4 4
2 2 1 1 4 4
1 2 3 2 2 2
1 2 2 4 4 3
2 2 3 3 3 3
2 1 1 2 1 3
1 1 1 1 3 2
1 1 1 1 1 5
2 2 2 3 3 3
3 2 1 2 2 1
2 2 3 3 2 2
2 2 3 1 1 2
3 3 3 4 4 4
2 2 2 2 2 2
2 2 2 2 2 1
2 3 2 3 2 5
2 2 2 2 2 3
2 2 3 3 3 4
2 2 2 2 3 2
4 4 4 2 4 4
2 2 2 2 3 2
2 1 1 2 2 2
3 3 2 2 3 3
2 2 2 2 2 2
3 2 2 1 4 2
2 2 2 2 2 2
3 4 4 1 4 4
4 2 2 3 4 4
4 3 4 3 3 2
2 2 2 2 3 2
4 4 4 2 5 4
1 2 1 2 2 3
1 3 4 3 2 4
1 2 3 3 3 3
3 2 2 3 4 4
2 2 2 1 2 2
3 2 3 3 4 3
2 2 4 4 3 4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269254&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269254&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269254&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







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)
1-0.691390-0.751174-0.74
2-0.761498-0.751382-0.73
3-0.522482-0.552364-0.47
4-0.71997-0.671872-0.6
50.0751430.0948360.14
6-0.264372-0.253757-0.21

\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 & -0.69 & 13 & 90 & -0.75 & 11 & 74 & -0.74 \tabularnewline
2 & -0.76 & 14 & 98 & -0.75 & 13 & 82 & -0.73 \tabularnewline
3 & -0.52 & 24 & 82 & -0.55 & 23 & 64 & -0.47 \tabularnewline
4 & -0.7 & 19 & 97 & -0.67 & 18 & 72 & -0.6 \tabularnewline
5 & 0.07 & 51 & 43 & 0.09 & 48 & 36 & 0.14 \tabularnewline
6 & -0.26 & 43 & 72 & -0.25 & 37 & 57 & -0.21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269254&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]-0.69[/C][C]13[/C][C]90[/C][C]-0.75[/C][C]11[/C][C]74[/C][C]-0.74[/C][/ROW]
[ROW][C]2[/C][C]-0.76[/C][C]14[/C][C]98[/C][C]-0.75[/C][C]13[/C][C]82[/C][C]-0.73[/C][/ROW]
[ROW][C]3[/C][C]-0.52[/C][C]24[/C][C]82[/C][C]-0.55[/C][C]23[/C][C]64[/C][C]-0.47[/C][/ROW]
[ROW][C]4[/C][C]-0.7[/C][C]19[/C][C]97[/C][C]-0.67[/C][C]18[/C][C]72[/C][C]-0.6[/C][/ROW]
[ROW][C]5[/C][C]0.07[/C][C]51[/C][C]43[/C][C]0.09[/C][C]48[/C][C]36[/C][C]0.14[/C][/ROW]
[ROW][C]6[/C][C]-0.26[/C][C]43[/C][C]72[/C][C]-0.25[/C][C]37[/C][C]57[/C][C]-0.21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269254&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269254&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)
1-0.691390-0.751174-0.74
2-0.761498-0.751382-0.73
3-0.522482-0.552364-0.47
4-0.71997-0.671872-0.6
50.0751430.0948360.14
6-0.264372-0.253757-0.21







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.995 (0)0.99 (0)
(Ps-Ns)/(Ps+Ns)0.995 (0)1 (0)0.997 (0)
(Pc-Nc)/(Pc+Nc)0.99 (0)0.997 (0)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) & 0.995 (0) & 0.99 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.995 (0) & 1 (0) & 0.997 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.99 (0) & 0.997 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269254&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]0.995 (0)[/C][C]0.99 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.995 (0)[/C][C]1 (0)[/C][C]0.997 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.99 (0)[/C][C]0.997 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269254&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269254&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)0.995 (0)0.99 (0)
(Ps-Ns)/(Ps+Ns)0.995 (0)1 (0)0.997 (0)
(Pc-Nc)/(Pc+Nc)0.99 (0)0.997 (0)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0.003)0.828 (0.022)0.733 (0.056)
(Ps-Ns)/(Ps+Ns)0.828 (0.022)1 (0.006)0.966 (0.007)
(Pc-Nc)/(Pc+Nc)0.733 (0.056)0.966 (0.007)1 (0.003)

\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 (0.003) & 0.828 (0.022) & 0.733 (0.056) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.828 (0.022) & 1 (0.006) & 0.966 (0.007) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.733 (0.056) & 0.966 (0.007) & 1 (0.003) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269254&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 (0.003)[/C][C]0.828 (0.022)[/C][C]0.733 (0.056)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.828 (0.022)[/C][C]1 (0.006)[/C][C]0.966 (0.007)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.733 (0.056)[/C][C]0.966 (0.007)[/C][C]1 (0.003)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269254&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269254&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 (0.003)0.828 (0.022)0.733 (0.056)
(Ps-Ns)/(Ps+Ns)0.828 (0.022)1 (0.006)0.966 (0.007)
(Pc-Nc)/(Pc+Nc)0.733 (0.056)0.966 (0.007)1 (0.003)



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):
par1 <- ''
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')