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Author*Unverified author*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationFri, 14 Sep 2012 13:12:00 -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/Sep/14/t1347642817hvpa6cnbc93ejp1.htm/, Retrieved Fri, 03 May 2024 16:26:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169624, Retrieved Fri, 03 May 2024 16:26:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [] [2012-09-14 17:12:00] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
6.00	27.89	'1'
16.00	21.38	'1'
13.00	34.93	'1'
15.00	28.09	'1'
14.00	32.39	'1'
14.00	36.17	'1'
20.00	40.06	'1'
20.00	41.73	'1'
16.00	29.90	'1'
8.00	27.43	'1'
7.00	18.40	'1'
9.00	29.03	'1'
13.00	25.72	'1'
9.00	32.86	'1'
10.00	28.04	'1'
24.00	31.80	'1'
5.00	23.80	'1'
22.00	27.68	'1'
15.00	32.41	'1'
20.00	24.83	'1'
13.00	37.15	'1'
15.00	24.60	'1'
5.00	22.40	'1'
16.00	16.65	'1'
28.00	26.47	'1'
5.00	28.50	'1'
13.00	25.80	'1'
13.00	37.30	'1'
18.00	39.56	'1'
17.00	28.50	'1'
6.00	24.17	'1'
9.00	19.40	'1'
10.00	26.67	'1'
8.00	25.10	'1'
24.00	33.09	'1'
19.00	38.20	'1'
20.00	27.51	'1'
29.00	33.34	'1'
23.00	23.94	'1'
24.00	31.45	'1'
23.00	23.65	'1'
22.00	22.79	'1'
22.00	41.42	'1'
26.00	22.62	'2'
20.00	32.89	'2'
14.00	37.88	'2'
25.00	23.33	'2'
19.00	39.10	'2'
14.00	35.33	'2'
10.00	23.94	'2'
7.00	37.41	'2'
9.00	24.03	'2'
10.00	27.60	'2'
15.00	26.58	'2'
27.00	38.13	'2'
25.00	42.92	'2'
20.00	29.92	'2'
10.00	49.42	'2'
23.00	27.43	'2'
18.00	24.88	'2'
15.00	32.27	'2'
21.00	24.16	'2'
19.00	30.14	'2'
19.00	27.83	'2'
11.00	36.71	'2'
24.00	29.65	'2'
12.00	21.33	'2'
8.00	29.09	'2'
4.00	22.68	'2'
9.00	26.84	'2'
8.00	27.03	'2'
10.00	21.09	'2'
15.00	24.03	'2'
23.00	37.56	'2'
25.00	29.47	'2'
13.00	28.50	'2'
30.00	30.93	'2'
22.00	24.31	'2'
11.00	36.98	'2'
17.00	26.17	'2'
17.00	25.47	'2'
11.00	28.20	'2'
13.00	27.33	'2'
7.00	21.95	'2'
17.00	23.28	'2'
28.00	27.91	'2'
23.00	28.14	'2'
18.00	27.12	'2'
21.00	23.33	'2'
15.00	23.13	'2'
22.00	29.10	'2'
17.00	26.50	'2'
26.00	26.25	'2'
7.00	26.20	'2'
15.00	27.60	'2'
23.00	31.90	'2'
14.00	43.28	'2'
11.00	23.47	'2'
34.00	27.70	'2'
20.00	26.40	'2'
21.00	24.60	'2'
15.00	33.80	'2'
13.00	27.60	'2'
14.00	19.26	'2'
27.00	35.20	'2'
12.00	27.30	'2'
20.00	33.60	'2'
30.00	26.47	'1'
11.00	26.21	'2'
19.00	26.90	'2'
22.00	17.20	'2'
15.00	32.08	'2'
12.00	29.70	'2'
11.00	21.26	'2'
17.00	38.30	'2'
16.00	20.50	'2'
20.00	26.03	'2'
13.00	28.24	'2'
9.00	28.18	'2'
14.00	30.38	'2'
13.00	31.29	'2'
10.00	24.02	'2'
21.00	28.96	'2'
28.00	25.65	'2'
10.00	28.49	'2'
16.00	38.58	'2'
10.00	26.37	'2'
19.00	22.28	'2'
25.00	23.40	'2'
16.00	22.74	'2'
13.00	25.10	'2'
24.00	29.97	'2'
19.00	28.24	'2'
22.00	26.28	'2'
23.00	29.76	'2'
23.00	31.70	'2'
11.00	35.58	'2'
15.00	21.90	'2'
11.00	53.55	'2'
28.00	27.00	'2'
18.00	26.41	'2'
17.00	25.99	'2'
19.00	25.80	'2'
25.00	30.44	'2'
16.00	29.68	'2'
17.00	34.48	'2'
18.00	27.39	'2'




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=169624&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=169624&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169624&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 = hA ; par2 = IMC ; par3 = Gen ; par4 = FALSE ;
Parameters (R input):
par1 = hA ; par2 = IMC ; par3 = Gen ; par4 = FALSE ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
cat3 <- as.numeric(par3)
intercept<-as.logical(par4)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
f2 <- as.character(x[,cat3])
xdf<-data.frame(x1,f1, f2)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
(V3 <-dimnames(y)[[1]][cat3])
names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, lmxdf$call['formula'],length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){
a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
for(i in 1 : length(rownames(anova.xdf))-1){
a<-table.row.start(a)
a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], digits=3),,FALSE)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$'Df'[i+1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups')
dev.off()
bitmap(file='designplot.png')
xdf2 <- xdf # to preserve xdf make copy for function
names(xdf2) <- c(V1, V2, V3)
plot.design(xdf2, main='Design Plot of Group Means')
dev.off()
bitmap(file='interactionplot.png')
interaction.plot(xdf$Treatment_A, xdf$Treatment_B, xdf$Response, xlab=V2, ylab=V1, trace.label=V3, main='Possible Interactions Between Anova Groups')
dev.off()
if(intercept==TRUE){
thsd<-TukeyHSD(aov.xdf)
names(thsd) <- c(V2, V3, paste(V2, ':', V3, sep=''))
bitmap(file='TukeyHSDPlot.png')
layout(matrix(c(1,2,3,3), 2,2))
plot(thsd, las=1)
dev.off()
}
if(intercept==TRUE){
ntables<-length(names(thsd))
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(nt in 1:ntables){
for(i in 1:length(rownames(thsd[[nt]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[nt]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[nt]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
} # end nt
a<-table.end(a)
table.save(a,file='hsdtable.tab')
}#end if hsd tables
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-levene.test(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')