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Description of Statistical Computation

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 computationWed, 25 Jan 2017 11:02:53 +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/2017/Jan/25/t1485338581rfuq7snfm7m5tjx.htm/, Retrieved Tue, 14 May 2024 16:36:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306536, Retrieved Tue, 14 May 2024 16:36:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact36

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [] [2017-01-25 10:02:53] [2afcbc313e2a613e91c73c4ef04af8e0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13 22 14 22 4 2 4 3 5 4
16 24 19 24 5 3 3 4 5 4
17 21 17 26 4 4 5 4 5 4
NA 21 17 21 3 4 3 3 4 4
NA 24 15 26 4 4 5 4 5 4
16 20 20 25 3 4 4 4 5 5
NA 22 15 21 3 4 4 3 3 4
NA 20 19 24 3 4 5 4 4 4
NA 19 15 27 4 5 4 4 5 5
17 23 15 28 4 5 5 4 5 5
17 21 19 23 4 4 2 4 5 4
15 19 NA 25 4 4 5 3 5 4
16 19 20 24 4 4 4 3 4 5
14 21 18 24 3 3 5 4 4 5
16 21 15 24 4 4 5 4 2 5
17 22 14 25 3 4 5 4 4 5
NA 22 20 25 3 4 5 4 4 5
NA 19 NA NA NA NA 5 NA 5 5
NA 21 16 25 5 5 4 3 4 4
NA 21 16 25 4 4 4 4 5 4
16 21 16 24 3 4 5 3 4 5
NA 20 10 26 4 4 4 4 5 5
16 22 19 26 4 4 5 4 4 5
NA 22 19 25 4 4 5 4 4 4
NA 24 16 26 4 4 5 4 4 5
NA 21 15 23 3 4 4 4 4 4
16 19 18 24 3 4 4 3 5 5
15 19 17 24 4 4 4 4 4 4
16 23 19 25 2 4 5 4 5 5
16 21 17 25 5 4 4 4 4 4
13 21 NA 24 4 3 5 4 4 4
15 19 19 28 4 5 5 4 5 5
17 21 20 27 5 4 5 4 4 5
NA 19 5 NA 4 3 5 4 NA 5
13 21 19 23 2 3 5 4 5 4
17 21 16 23 4 5 2 4 4 4
NA 23 15 24 3 4 5 4 4 4
14 19 16 24 4 3 5 3 4 5
14 19 18 22 4 3 3 4 4 4
18 19 16 25 4 4 5 4 4 4
NA 18 15 25 5 4 4 4 4 4
17 22 17 28 4 5 5 4 5 5
13 18 NA 22 3 3 4 4 4 4
16 22 20 28 5 5 5 3 5 5
15 18 19 25 5 4 5 3 4 4
15 22 7 24 4 4 4 3 4 5
NA 22 13 24 4 4 4 4 4 4
15 19 16 23 3 5 5 3 3 4
13 22 16 25 4 4 4 4 5 4
NA 25 NA NA 2 3 4 2 NA 4
17 19 18 26 4 5 5 4 4 4
NA 19 18 25 5 5 2 4 5 4
NA 19 16 27 5 5 5 4 4 4
11 19 17 26 4 3 5 4 5 5
14 21 19 23 4 3 4 3 4 5
13 21 16 25 4 4 5 4 4 4
NA 20 19 21 3 4 4 3 3 4
17 19 13 22 3 4 4 4 4 3
16 19 16 24 4 4 4 3 5 4
NA 22 13 25 4 4 4 4 5 4
17 26 12 27 5 5 3 4 5 5
16 19 17 24 2 4 4 4 5 5
16 21 17 26 4 4 4 4 5 5
16 21 17 21 3 4 4 4 2 4
15 20 16 27 4 4 5 4 5 5
12 23 16 22 4 2 4 4 4 4
17 22 14 23 4 4 4 3 5 3
14 22 16 24 4 4 4 3 5 4
14 22 13 25 5 4 5 3 3 5
16 21 16 24 3 4 4 3 5 5
NA 21 14 23 3 4 4 3 4 5
NA 22 20 28 4 5 5 5 5 4
NA 23 12 NA 4 4 3 4 NA 4
NA 18 13 24 4 4 4 4 4 4
NA 24 18 26 4 4 4 5 5 4
15 22 14 22 3 4 3 4 4 4
16 21 19 25 4 4 4 4 5 4
14 21 18 25 3 4 5 3 5 5
15 21 14 24 3 3 5 4 4 5
17 23 18 24 4 3 5 4 4 4
NA 21 19 26 4 4 5 4 4 5
10 23 15 21 3 3 3 4 4 4
NA 21 14 25 4 4 4 4 5 4
17 19 17 25 4 4 3 4 5 5
NA 21 19 26 4 4 4 4 5 5
20 21 13 25 5 4 4 4 4 4
17 21 19 26 5 4 3 5 4 5
18 23 18 27 4 4 5 4 5 5
NA 23 20 25 3 4 5 4 4 5
17 20 15 NA 3 NA 4 4 4 4
14 20 15 20 4 2 3 3 4 4
NA 19 15 24 4 4 5 4 4 3
17 23 20 26 4 4 5 4 4 5
NA 22 15 25 4 4 4 4 5 4
17 19 19 25 4 5 4 4 5 3
NA 23 18 24 3 4 4 3 5 5
16 22 18 26 4 4 5 4 4 5
18 22 15 25 5 4 3 4 4 5
18 21 20 28 5 4 5 5 4 5
16 21 17 27 4 5 4 4 5 5
NA 21 12 25 3 4 5 4 4 5
NA 21 18 26 5 3 4 4 5 5
15 22 19 26 4 4 5 4 4 5
13 25 20 26 5 4 4 4 4 5
NA 21 NA NA 3 4 4 3 NA 4
NA 23 17 28 5 4 4 5 5 5
NA 19 15 NA 4 4 5 3 NA 5
NA 22 16 21 4 4 3 3 4 3
NA 20 18 25 4 4 5 4 4 4
16 21 18 25 4 4 5 4 4 4
NA 25 14 24 3 4 5 4 5 3
NA 21 15 24 4 4 4 4 4 4
NA 19 12 24 4 4 4 3 4 5
12 23 17 23 3 3 4 3 5 5
NA 22 14 23 4 4 4 3 4 4
16 21 18 24 3 4 5 4 4 4
16 24 17 24 4 4 5 4 3 4
NA 21 17 25 5 4 5 1 5 5
16 19 20 28 5 4 5 4 5 5
14 18 16 23 4 4 4 4 4 3
15 19 14 24 4 4 5 3 4 4
14 20 15 23 3 4 4 3 4 5
NA 19 18 24 4 4 4 4 4 4
15 22 20 25 4 4 4 4 5 4
NA 21 17 24 4 5 3 4 4 4
15 22 17 23 3 4 4 4 4 4
16 24 17 23 4 4 4 3 4 4
NA 28 17 25 4 4 4 4 4 5
NA 19 15 21 3 4 3 3 4 4
NA 18 17 22 4 4 4 3 4 3
11 23 18 19 3 2 4 2 4 4
NA 19 17 24 4 4 4 3 5 4
18 23 20 25 5 4 4 3 5 4
NA 19 15 21 2 4 4 3 3 5
11 22 16 22 3 3 4 4 4 4
NA 21 15 23 4 4 4 3 4 4
18 19 18 27 5 5 4 4 5 4
NA 22 11 NA NA NA 2 NA NA NA
15 21 15 26 4 5 5 4 4 4
19 23 18 29 5 5 5 5 5 4
17 22 20 28 4 5 5 4 5 5
NA 19 19 24 4 4 4 3 4 5
14 19 14 25 3 4 5 4 5 4
NA 21 16 25 4 4 5 4 4 4
13 22 15 22 4 4 2 4 4 4
17 21 17 25 4 4 3 4 5 5
14 20 18 26 4 4 4 4 5 5
19 23 20 26 5 4 5 3 5 4
14 22 17 24 4 3 5 4 4 4
NA 23 18 25 4 4 5 4 4 4
NA 22 15 19 3 3 2 3 4 4
16 21 16 25 4 5 5 4 4 3
16 20 11 23 4 4 4 3 4 4
15 18 15 25 4 4 4 4 4 5
12 18 18 25 3 4 5 3 5 5
NA 20 17 26 4 4 5 4 4 5
17 19 16 27 5 4 5 4 5 4
NA 21 12 24 4 4 5 4 3 4
NA 24 19 22 2 3 5 4 4 4
18 19 18 25 4 4 4 4 4 5
15 20 15 24 4 3 4 3 5 5
18 19 17 23 4 4 4 4 4 3
15 23 19 27 4 5 5 5 4 4
NA 22 18 24 5 4 3 4 4 4
NA 21 19 24 5 4 4 3 4 4
NA 24 16 21 3 3 1 4 5 5
16 21 16 25 4 4 4 4 4 5
NA 21 16 25 4 4 4 4 5 4
16 22 14 23 2 3 4 5 5 4

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time5 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306536&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]5 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306536&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306536&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R ServerBig Analytics Cloud Computing Center






ANOVA Model
Response ~ Treatment_A * Treatment_B - 1
means17.519.51617.5161818.51317NA-2-0.4-2.5-3.5-2.5-5.5-2.50-1-4.5NANANANANANANANA-0.5NA4.5NANANANANA-4.6NA-2.1NANANANANANA1.50.52-2NANANA02.51.6670.167-2.5NANANA-1.6NA1.3331.833-3.5NANANA2.63.535.53.75NANANA-1NA0.420NANANA-3.5NANANANANANANANANANANANANANANANANANANANANANANA

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B - 1 \tabularnewline
means & 17.5 & 19.5 & 16 & 17.5 & 16 & 18 & 18.5 & 13 & 17 & NA & -2 & -0.4 & -2.5 & -3.5 & -2.5 & -5.5 & -2.5 & 0 & -1 & -4.5 & NA & NA & NA & NA & NA & NA & NA & NA & -0.5 & NA & 4.5 & NA & NA & NA & NA & NA & -4.6 & NA & -2.1 & NA & NA & NA & NA & NA & NA & 1.5 & 0.5 & 2 & -2 & NA & NA & NA & 0 & 2.5 & 1.667 & 0.167 & -2.5 & NA & NA & NA & -1.6 & NA & 1.333 & 1.833 & -3.5 & NA & NA & NA & 2.6 & 3.5 & 3 & 5.5 & 3.75 & NA & NA & NA & -1 & NA & 0.4 & 2 & 0 & NA & NA & NA & -3.5 & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306536&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]Response ~ Treatment_A * Treatment_B - 1[/C][/ROW]
[ROW][C]means[/C][C]17.5[/C][C]19.5[/C][C]16[/C][C]17.5[/C][C]16[/C][C]18[/C][C]18.5[/C][C]13[/C][C]17[/C][C]NA[/C][C]-2[/C][C]-0.4[/C][C]-2.5[/C][C]-3.5[/C][C]-2.5[/C][C]-5.5[/C][C]-2.5[/C][C]0[/C][C]-1[/C][C]-4.5[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]-0.5[/C][C]NA[/C][C]4.5[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]-4.6[/C][C]NA[/C][C]-2.1[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]1.5[/C][C]0.5[/C][C]2[/C][C]-2[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]0[/C][C]2.5[/C][C]1.667[/C][C]0.167[/C][C]-2.5[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]-1.6[/C][C]NA[/C][C]1.333[/C][C]1.833[/C][C]-3.5[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]2.6[/C][C]3.5[/C][C]3[/C][C]5.5[/C][C]3.75[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]-1[/C][C]NA[/C][C]0.4[/C][C]2[/C][C]0[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]-3.5[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306536&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306536&T=1

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Model
Response ~ Treatment_A * Treatment_B - 1
means17.519.51617.5161818.51317NA-2-0.4-2.5-3.5-2.5-5.5-2.50-1-4.5NANANANANANANANA-0.5NA4.5NANANANANA-4.6NA-2.1NANANANANANA1.50.52-2NANANA02.51.6670.167-2.5NANANA-1.6NA1.3331.833-3.5NANANA2.63.535.53.75NANANA-1NA0.420NANANA-3.5NANANANANANANANANANANANANANANANANANANANANANANA






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
9
Treatment_A924702.5692744.73827.5570
Treatment_B944.3774.4381.3380.233
Treatment_A:Treatment_B990.0043.3331.0050.478
Residuals57189.053.317 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 9 &  &  &  &  \tabularnewline
Treatment_A & 9 & 24702.569 & 2744.73 & 827.557 & 0 \tabularnewline
Treatment_B & 9 & 44.377 & 4.438 & 1.338 & 0.233 \tabularnewline
Treatment_A:Treatment_B & 9 & 90.004 & 3.333 & 1.005 & 0.478 \tabularnewline
Residuals & 57 & 189.05 & 3.317 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306536&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]9[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]9[/C][C]24702.569[/C][C]2744.73[/C][C]827.557[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]9[/C][C]44.377[/C][C]4.438[/C][C]1.338[/C][C]0.233[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]9[/C][C]90.004[/C][C]3.333[/C][C]1.005[/C][C]0.478[/C][/ROW]
[ROW][C]Residuals[/C][C]57[/C][C]189.05[/C][C]3.317[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306536&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306536&T=2

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
9
Treatment_A924702.5692744.73827.5570
Treatment_B944.3774.4381.3380.233
Treatment_A:Treatment_B990.0043.3331.0050.478
Residuals57189.053.317






Must Include Intercept to use Tukey Test 

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306536&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306536&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306536&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Must Include Intercept to use Tukey Test






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group450.9830.52
57 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 45 & 0.983 & 0.52 \tabularnewline
  & 57 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306536&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]45[/C][C]0.983[/C][C]0.52[/C][/ROW]
[ROW][C] [/C][C]57[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306536&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306536&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group450.9830.52
57


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 3 ; 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')