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Author's title

Author*Unverified author*
R Software Modulerwasp_Mixed Model ANOVA.wasp
Title produced by softwareMixed Within-Between Two-Way ANOVA
Date of computationWed, 19 Oct 2016 22:24:36 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Oct/19/t1476912365y3vdswicyp3i1id.htm/, Retrieved Tue, 30 Apr 2024 09:35:08 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Tue, 30 Apr 2024 09:35:08 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
Group	Phage %	Kill %	Lyt 1	 IL6	 IL2	 TNF
A1(+ve)	76.1	72.2	1.16	536.54	195.41	182.08
	72.8	74.1	1.07	421.12	182.98	170.91
	80.5	66.5	1.32	530.59	201.55	193.43
A2	76.23	74.2	1.28	465.11	193.61	169.41
	73.18	71.3	1.12	466.01	187.8	157.98
	80.11	76.8	1.23	465.27	178.26	178.76
A3	79.3	75.8	1.42	379.68	188.15	165.73
	76.4	70.2	1.22	358.96	175.81	156.12
	85.1	80.5	1.57	385.21	198.27	171.55
A4	80.27	77.2	1.44	405.77	180.09	167.09
	76.39	71.5	1.37	420.21	170.21	168.87
	85.87	80.1	1.57	390.65	189.54	173.11
A5 (-)	89	85.4	1.72	239.43	161.61	136.94
	85.2	79.5	0.98	226.99	169.87	149.8
	93.8	89.9	2.2	250.22	170.92	129.44




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

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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' @ jenkins.wessa.net



Parameters (Session):
par1 = 5 ; par2 = 3 ; par3 = 4 ; par4 = 2 ; par5 = 1 ;
Parameters (R input):
par1 = 5 ; par2 = 3 ; par3 = 4 ; par4 = 2 ; par5 = 1 ;
R code (references can be found in the software module):
par5 <- '1'
par4 <- '2'
par3 <- '4'
par2 <- '3'
par1 <- '5'
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
cat3 <- as.numeric(par3)
cat4 <-as.numeric(par4)
cat5 <-as.numeric(par5)
x <- t(x)
x1<-as.numeric(x[,cat1])
wf1<-as.character(x[,cat2])
wf2 <- as.character(x[,cat3])
bf1 <- as.character(x[,cat4])
sid<- as.character(x[,cat5]) # author of ez changed within subjects variable name from sid to wid
xdf<-data.frame(x1,wf1, wf2, bf1, sid)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
(V3 <-dimnames(y)[[1]][cat3])
(V4 <-dimnames(y)[[1]][cat4])
(V5 <-dimnames(y)[[1]][cat5])
names(xdf)<-c(V1, V2, V3, V4, V5)
library(ez)
library(Cairo)
(ezout <- ezANOVA(data=xdf, dv=.(mean_rt), wid=.(sid), within=.(cue, flanker), between=.(group) ) )
load(file='createtable')
a<-table.start()
nr <- nrow(ezout$ANOVA)
nc <- ncol(ezout$ANOVA)
a<-table.row.start(a)
a<-table.element(a,'Repeated Measures ANOVA', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'effect', 1,TRUE)
a<-table.element(a,'Dfn',1,TRUE)
a<-table.element(a,'DFd', 1,TRUE)
a<-table.element(a, 'F', 1,TRUE)
a<-table.element(a,'p', 1,TRUE)
a<-table.element(a,'p<0.05', 1,TRUE)
a<-table.element(a, 'ges', 1,TRUE) # generalized eta-sq - was partial eta-sq in earlier version
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezout$ANOVA$Effect[i], 1, TRUE)
for(j in 2:nc){
if ( j != 6) # author of ez reduced number of columns in output from 8
a<-table.element(a,round(ezout$ANOVA[[j]][i], digits=3), 1, FALSE)
else a<-table.element(a, ezout$ANOVA[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
nr <- nrow(ezout$Mauchly)
nc <- ncol(ezout$Mauchly)
a<-table.row.start(a)
a<-table.element(a,'Mauchlys Test for Sphericity', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'effect', 1,TRUE)
a<-table.element(a,'W',1,TRUE)
a<-table.element(a,'p', 1,TRUE)
a<-table.element(a,'p<0.05', 1,TRUE)
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezout$Mauchly$Effect[i], 1, TRUE)
for(j in 2:nc){
if (j != 4)
a<-table.element(a,round(ezout$Mauchly[[j]][i], digits = 3), 1, FALSE)
else
a<-table.element(a,ezout$Mauchly[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
nr <- nrow(ezout$Spher)
nc <- ncol(ezout$Sphe)
a<-table.row.start(a)
a<-table.element(a,'Sphericity Corrections', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'effect', 1,TRUE)
a<-table.element(a,'GGe',1,TRUE)
a<-table.element(a,'p[GG]', 1,TRUE)
a<-table.element(a,'p[GG]<0.05', 1,TRUE)
a<-table.element(a,'HFe', 1,TRUE)
a<-table.element(a,'p[HF]', 1,TRUE)
a<-table.element(a,'p[HF]<0.05', 1,TRUE)
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezout$Spher$Effect[i], 1, TRUE)
for(j in 2:nc){
if ( ! ((j == 4) | (j == 7)) )
a<-table.element(a,round(ezout$Spher[[j]][i], digits=3), 1, FALSE)
else
a<-table.element(a,ezout$Spher[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
ezP.between<-ezPlot(data = xdf, dv = .(mean_rt), between = .(group), wid = .(sid), do_lines=FALSE, x_lab='group', y_lab='RT' , x=.(group))
bitmap(file = 'between.cairo')
print(ezP.between)
dev.off()
ezstats_between<-ezStats(data = xdf, dv = .(mean_rt), between =.(group), wid = .(sid))
a<-table.start()
nr <- nrow(ezstats_between)
nc <- ncol(ezstats_between)
a<-table.row.start(a)
a<-table.element(a,'Between Effects Comparisons', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
for(i in 1:nc){
a<-table.element(a, names(ezstats_between)[i], 1,TRUE)
}
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezstats_between[[1]][i], 1, TRUE)
for(j in 2:nc){
a<-table.element(a,ezstats_between[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable3.tab')
ezP.within<-ezPlot(data = xdf, dv = .(mean_rt), within = .(cue, flanker), wid = .(sid), do_lines=TRUE, x_lab='flanker', y_lab='RT' , x=.(flanker), split=.(cue), split_lab = 'cue')
bitmap(file = 'within.cairo')
print(ezP.within)
dev.off()
ezstats_within <- ezStats(data = xdf, dv = .(mean_rt), within = .(cue, flanker), wid = .(sid))
a<-table.start()
nr <- nrow(ezstats_within)
nc <- ncol(ezstats_within)
a<-table.row.start(a)
a<-table.element(a,'Within Effects Comparisons', nc+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
for(i in 1:nc){
a<-table.element(a, names(ezstats_within)[i], 1,TRUE)
}
a<-table.row.end(a)
for ( i in 1:nr){
a<-table.row.start(a)
a<-table.element(a,ezstats_within[[1]][i], 1, TRUE)
for(j in 2:nc){
a<-table.element(a, ezstats_within[[j]][i], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')