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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_Two Factor ANOVA.wasp
Title produced by softwareTwo-Way ANOVA
Date of computationMon, 17 Dec 2012 07:59:21 -0500
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/Dec/17/t13557492401kbk230zr8qjybp.htm/, Retrieved Thu, 28 Mar 2024 18:09:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=200828, Retrieved Thu, 28 Mar 2024 18:09:23 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [] [2010-11-02 14:42:14] [b98453cac15ba1066b407e146608df68]
- R PD    [Two-Way ANOVA] [paper deel 5 anova] [2012-12-17 12:59:21] [7915dafcfdccff56a257085e1714b048] [Current]
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Dataseries X:
4	1	'Treatment'	0	'No'	0	1
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	1	'NoTreatment'	0	'No'	1	1
4	0	'NoTreatment'	0	'No'	0	0
4	0	'Treatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	1
4	1	'NoTreatment'	0	'No'	0	0
4	1	'Treatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	1	'No'	1	0
4	1	'Treatment'	0	'No'	0	0
4	0	'NoTreatment'	1	'No'	1	1
4	0	'Treatment'	1	'No'	1	1
4	1	'Treatment'	1	'Yes'	1	0
4	1	'Treatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	1
4	0	'Treatment'	1	'Yes'	1	1
4	1	'NoTreatment'	0	'No'	1	0
4	1	'NoTreatment'	1	'No'	1	1
4	0	'NoTreatment'	0	'No'	1	1
4	1	'NoTreatment'	0	'No'	1	1
4	0	'Treatment'	1	'No'	0	1
4	0	'NoTreatment'	1	'No'	1	0
4	1	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	1	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	0	'No'	1	0
4	0	'NoTreatment'	0	'No'	0	0
4	1	'NoTreatment'	0	'No'	0	0
4	1	'NoTreatment'	0	'No'	1	0
4	0	'Treatment'	0	'No'	0	1
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	1	'Treatment'	1	'No'	1	0
4	0	'NoTreatment'	1	'No'	0	1
4	0	'NoTreatment'	0	'No'	1	1
4	0	'Treatment'	0	'No'	1	0
4	0	'NoTreatment'	1	'Yes'	1	1
4	0	'NoTreatment'	1	'No'	0	1
4	1	'NoTreatment'	0	'No'	1	1
4	1	'Treatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	1	0
4	0	'NoTreatment'	0	'No'	1	1
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	0	'No'	1	1
4	0	'NoTreatment'	0	'No'	0	0
4	0	'Treatment'	1	'No'	0	0
4	1	'Treatment'	1	'Yes'	1	0
4	0	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	1	'Yes'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	0	'Treatment'	1	'No'	0	1
4	0	'NoTreatment'	1	'No'	1	1
4	0	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	0	'No'	0	1
4	1	'Treatment'	1	'Yes'	1	1
4	1	'Treatment'	0	'No'	0	1
4	0	'NoTreatment'	1	'No'	1	0
4	0	'NoTreatment'	0	'No'	0	0
4	1	'Treatment'	0	'No'	0	1
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	0	'Treatment'	1	'Yes'	1	0
4	1	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	1	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	1	'No'	0	1
4	1	'NoTreatment'	1	'No'	0	0
4	0	'NoTreatment'	0	'No'	0	1
4	0	'Treatment'	0	'No'	1	1
4	0	'NoTreatment'	0	'No'	0	1
4	0	'NoTreatment'	1	'No'	1	1
4	0	'Treatment'	1	'Yes'	0	1
4	0	'Treatment'	0	'No'	1	0
4	0	'NoTreatment'	0	'No'	0	0
4	1	'NoTreatment'	1	'No'	0	1
4	0	'NoTreatment'	0	'No'	0	0
4	0	'NoTreatment'	1	'Yes'	0	0
4	0	'NoTreatment'	0	'No'	1	1
4	1	'NoTreatment'	0	'No'	0	0
2	1	'NoTreatment'	0	'No'	0	1
2	1	'Treatment'	1	'No'	0	1
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	1
2	0	'NoTreatment'	0	'No'	1	0
2	1	'Treatment'	0	'No'	0	0
2	1	'NoTreatment'	0	'No'	1	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'Treatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	1
2	1	'Treatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	1	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	1
2	1	'NoTreatment'	0	'No'	0	1
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'Treatment'	1	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	1	'Treatment'	1	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	1	'NoTreatment'	0	'No'	0	0
2	1	'Treatment'	1	'No'	1	0
2	0	'Treatment'	0	'No'	0	0
2	0	'NoTreatment'	1	'No'	0	0
2	1	'Treatment'	1	'No'	0	0
2	1	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	1	'NoTreatment'	0	'No'	0	1
2	1	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	1
2	1	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	1	'Treatment'	1	'No'	0	0
2	0	'NoTreatment'	1	'No'	1	1
2	0	'NoTreatment'	0	'No'	0	1
2	0	'Treatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	1	0
2	0	'NoTreatment'	0	'No'	0	1
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	1
2	1	'NoTreatment'	0	'No'	0	0
2	1	'NoTreatment'	0	'No'	0	1
2	1	'NoTreatment'	1	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	1	'NoTreatment'	1	'No'	1	1
2	1	'Treatment'	1	'No'	1	1
2	0	'Treatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	1	'Yes'	0	1
2	0	'Treatment'	1	'No'	0	1
2	1	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	1	1
2	0	'NoTreatment'	0	'No'	1	0
2	0	'Treatment'	0	'No'	0	1
2	0	'Treatment'	1	'No'	0	0
2	0	'Treatment'	0	'No'	0	0
2	1	'NoTreatment'	0	'No'	0	0
2	0	'NoTreatment'	0	'No'	1	1
2	0	'NoTreatment'	0	'No'	0	1
2	1	'NoTreatment'	1	'Yes'	0	0
2	1	'NoTreatment'	1	'Yes'	1	0
2	1	'NoTreatment'	1	'No'	0	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200828&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]4 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=200828&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200828&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 time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.25-0.0440.0830.544

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 0.25 & -0.044 & 0.083 & 0.544 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200828&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]0.25[/C][C]-0.044[/C][C]0.083[/C][C]0.544[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200828&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200828&T=1

As an alternative you can also use a QR Code:  

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

ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.25-0.0440.0830.544







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A10.0620.0620.330.566
Treatment_B11.2511.2516.710.011
Treatment_A:Treatment_B10.7960.7964.2670.041
Residuals15027.9750.187

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 0.062 & 0.062 & 0.33 & 0.566 \tabularnewline
Treatment_B & 1 & 1.251 & 1.251 & 6.71 & 0.011 \tabularnewline
Treatment_A:Treatment_B & 1 & 0.796 & 0.796 & 4.267 & 0.041 \tabularnewline
Residuals & 150 & 27.975 & 0.187 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200828&T=2

[TABLE]
[ROW][C]ANOVA Statistics[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]Sum Sq[/C][C]Mean Sq[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C][/C][C]1[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]1[/C][C]0.062[/C][C]0.062[/C][C]0.33[/C][C]0.566[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]1.251[/C][C]1.251[/C][C]6.71[/C][C]0.011[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]0.796[/C][C]0.796[/C][C]4.267[/C][C]0.041[/C][/ROW]
[ROW][C]Residuals[/C][C]150[/C][C]27.975[/C][C]0.187[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200828&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200828&T=2

As an alternative you can also use a QR Code:  

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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A10.0620.0620.330.566
Treatment_B11.2511.2516.710.011
Treatment_A:Treatment_B10.7960.7964.2670.041
Residuals15027.9750.187







Tukey Honest Significant Difference Comparisons
difflwruprp adj
Treatment-NoTreatment0.046-0.1110.2020.566
Yes-No0.3320.0750.5890.012
Treatment:No-NoTreatment:No-0.044-0.2650.1770.954
NoTreatment:Yes-NoTreatment:No0.083-0.3870.5540.968
Treatment:Yes-NoTreatment:No0.5830.1131.0540.008
NoTreatment:Yes-Treatment:No0.127-0.3690.6240.91
Treatment:Yes-Treatment:No0.6270.1311.1240.007
Treatment:Yes-NoTreatment:Yes0.5-0.1481.1480.191

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
Treatment-NoTreatment & 0.046 & -0.111 & 0.202 & 0.566 \tabularnewline
Yes-No & 0.332 & 0.075 & 0.589 & 0.012 \tabularnewline
Treatment:No-NoTreatment:No & -0.044 & -0.265 & 0.177 & 0.954 \tabularnewline
NoTreatment:Yes-NoTreatment:No & 0.083 & -0.387 & 0.554 & 0.968 \tabularnewline
Treatment:Yes-NoTreatment:No & 0.583 & 0.113 & 1.054 & 0.008 \tabularnewline
NoTreatment:Yes-Treatment:No & 0.127 & -0.369 & 0.624 & 0.91 \tabularnewline
Treatment:Yes-Treatment:No & 0.627 & 0.131 & 1.124 & 0.007 \tabularnewline
Treatment:Yes-NoTreatment:Yes & 0.5 & -0.148 & 1.148 & 0.191 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200828&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C] [/C][C]diff[/C][C]lwr[/C][C]upr[/C][C]p adj[/C][/ROW]
[ROW][C]Treatment-NoTreatment[/C][C]0.046[/C][C]-0.111[/C][C]0.202[/C][C]0.566[/C][/ROW]
[ROW][C]Yes-No[/C][C]0.332[/C][C]0.075[/C][C]0.589[/C][C]0.012[/C][/ROW]
[ROW][C]Treatment:No-NoTreatment:No[/C][C]-0.044[/C][C]-0.265[/C][C]0.177[/C][C]0.954[/C][/ROW]
[ROW][C]NoTreatment:Yes-NoTreatment:No[/C][C]0.083[/C][C]-0.387[/C][C]0.554[/C][C]0.968[/C][/ROW]
[ROW][C]Treatment:Yes-NoTreatment:No[/C][C]0.583[/C][C]0.113[/C][C]1.054[/C][C]0.008[/C][/ROW]
[ROW][C]NoTreatment:Yes-Treatment:No[/C][C]0.127[/C][C]-0.369[/C][C]0.624[/C][C]0.91[/C][/ROW]
[ROW][C]Treatment:Yes-Treatment:No[/C][C]0.627[/C][C]0.131[/C][C]1.124[/C][C]0.007[/C][/ROW]
[ROW][C]Treatment:Yes-NoTreatment:Yes[/C][C]0.5[/C][C]-0.148[/C][C]1.148[/C][C]0.191[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200828&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200828&T=3

As an alternative you can also use a QR Code:  

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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
Treatment-NoTreatment0.046-0.1110.2020.566
Yes-No0.3320.0750.5890.012
Treatment:No-NoTreatment:No-0.044-0.2650.1770.954
NoTreatment:Yes-NoTreatment:No0.083-0.3870.5540.968
Treatment:Yes-NoTreatment:No0.5830.1131.0540.008
NoTreatment:Yes-Treatment:No0.127-0.3690.6240.91
Treatment:Yes-Treatment:No0.6270.1311.1240.007
Treatment:Yes-NoTreatment:Yes0.5-0.1481.1480.191







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.2410.868
150

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.241 & 0.868 \tabularnewline
  & 150 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200828&T=4

[TABLE]
[ROW][C]Levenes Test for Homogeneity of Variance[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Group[/C][C]3[/C][C]0.241[/C][C]0.868[/C][/ROW]
[ROW][C] [/C][C]150[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200828&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200828&T=4

As an alternative you can also use a QR Code:  

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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.2410.868
150



Parameters (Session):
par1 = 6 ; par2 = 3 ; par3 = 5 ; par4 = TRUE ;
Parameters (R input):
par1 = 6 ; par2 = 3 ; par3 = 5 ; par4 = TRUE ;
R code (references can be found in the software module):
par4 <- 'FALSE'
par3 <- '6'
par2 <- '3'
par1 <- '5'
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')