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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, 17 Dec 2014 19:49:10 +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/17/t1418845790xs9rn3bnxcdrjy9.htm/, Retrieved Thu, 16 May 2024 17:32:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270618, Retrieved Thu, 16 May 2024 17:32:18 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [] [2014-12-17 19:49:10] [18673d63f90870b9c004059cd6229007] [Current]
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Dataseries X:
'S' 1 7.5 149 21
'S' 0 6 139 22
'S' 1 6.5 148 22
'S' 0 1 158 18
'S' 1 1 128 23
'S' 1 5.5 224 12
'S' 1 8.5 159 20
'S' 0 6.5 105 22
'S' 1 4.5 159 21
'S' 1 2 167 19
'S' 1 5 165 22
'S' 1 0.5 159 15
'S' 1 5 119 20
'S' 1 5 176 19
'S' 0 2.5 54 18
'B' 0 5 91 15
'S' 0 5.5 163 20
'S' 1 3.5 124 21
'B' 0 3 137 21
'S' 1 4 121 15
'S' 0 0.5 153 16
'S' 1 6.5 148 23
'S' 1 4.5 221 21
'S' 0 7.5 188 18
'S' 1 5.5 149 25
'S' 1 4 244 9
'B' 1 7.5 148 30
'B' 1 7 92 20
'S' 0 4 150 23
'S' 1 5.5 153 16
'S' 0 2.5 94 16
'S' 0 5.5 156 19
'S' 1 3.5 132 25
'S' 1 2.5 161 18
'S' 1 4.5 105 23
'S' 1 4.5 97 21
'S' 1 4.5 151 10
'B' 0 6 131 14
'S' 1 2.5 166 22
'S' 1 5 157 26
'S' 0 0 111 23
'S' 1 5 145 23
'S' 1 6.5 162 24
'S' 1 5 163 24
'B' 1 6 59 18
'S' 1 4.5 187 23
'S' 0 5.5 109 15
'B' 1 1 90 19
'S' 1 7.5 105 16
'B' 0 6 83 25
'B' 1 5 116 23
'B' 1 1 42 17
'S' 1 5 148 19
'B' 1 6.5 155 21
'S' 1 7 125 18
'S' 1 4.5 116 27
'B' 1 0 128 21
'S' 0 8.5 138 13
'B' 1 3.5 49 8
'B' 0 7.5 96 29
'S' 1 3.5 164 28
'S' 1 6 162 23
'S' 0 1.5 99 21
'S' 0 9 202 19
'S' 1 3.5 186 19
'B' 0 3.5 66 20
'S' 1 4 183 18
'S' 0 6.5 214 19
'S' 1 7.5 188 17
'B' 1 6 104 19
'S' 0 5 177 25
'S' 0 5.5 126 19
'B' 0 3.5 76 22
'B' 0 7.5 99 23
'S' 1 6.5 139 14
'S' 1 6.5 162 16
'B' 0 6.5 108 24
'S' 1 7 159 20
'B' 0 3.5 74 12
'S' 0 1.5 110 24
'B' 1 4 96 22
'B' 0 7.5 116 12
'B' 0 4.5 87 22
'B' 0 0 97 20
'B' 1 3.5 127 10
'B' 0 5.5 106 23
'B' 1 5 80 17
'B' 1 4.5 74 22
'B' 0 2.5 91 24
'B' 0 7.5 133 18
'B' 0 7 74 21
'B' 1 0 114 20
'B' 1 4.5 140 20
'B' 1 3 95 22
'B' 0 1.5 98 19
'B' 1 3.5 121 20
'B' 0 2.5 126 26
'B' 1 5.5 98 23
'B' 1 8 95 24
'B' 1 1 110 21
'B' 1 5 70 21
'B' 1 4.5 102 19
'B' 0 3 86 8
'B' 1 3 130 17
'B' 1 8 96 20
'B' 1 2.5 102 11
'B' 0 7 100 8
'B' 0 0 94 15
'B' 0 1 52 18
'B' 0 3.5 98 18
'B' 0 5.5 118 19
'B' 0 5.5 99 19
'S' 1 0.5 48 23
'S' 1 7.5 50 22
'S' 1 9 150 21
'S' 1 9.5 154 25
'B' 1 8.5 109 30
'B' 0 7 68 17
'S' 1 8 194 27
'S' 1 10 158 23
'S' 0 7 159 23
'S' 1 8.5 67 18
'S' 0 9 147 18
'S' 0 9.5 39 23
'S' 1 4 100 19
'S' 1 6 111 15
'S' 1 8 138 20
'S' 1 5.5 101 16
'B' 1 9.5 131 24
'S' 1 7.5 101 25
'S' 1 7 114 25
'S' 1 7.5 165 19
'S' 0 8 114 19
'S' 1 7 111 16
'S' 1 7 75 19
'S' 1 6 82 19
'S' 1 10 121 23
'S' 1 2.5 32 21
'S' 1 9 150 22
'S' 0 8 117 19
'B' 1 6 71 20
'S' 1 8.5 165 20
'S' 1 6 154 3
'S' 1 9 126 23
'S' 0 8 149 23
'S' 0 9 145 20
'S' 0 5.5 120 15
'S' 0 7 109 16
'S' 0 5.5 132 7
'S' 0 9 172 24
'S' 1 2 169 17
'S' 0 8.5 114 24
'S' 1 9 156 24
'S' 1 8.5 172 19
'B' 0 9 68 25
'B' 1 7.5 89 20
'S' 1 10 167 28
'S' 1 9 113 23
'B' 0 7.5 115 27
'B' 0 6 78 18
'B' 0 10.5 118 28
'B' 0 8.5 87 21
'S' 1 8 173 19
'S' 0 10 2 23
'B' 1 10.5 162 27
'B' 0 6.5 49 22
'B' 1 9.5 122 28
'B' 0 8.5 96 25
'B' 1 7.5 100 21
'B' 0 5 82 22
'B' 0 8 100 28
'B' 1 10 115 20
'B' 0 7 141 29
'S' 1 7.5 165 25
'S' 1 7.5 165 25
'B' 1 9.5 110 20
'S' 1 6 118 20
'S' 1 10 158 16
'B' 0 7 146 20
'S' 1 3 49 20
'B' 0 6 90 23
'B' 0 7 121 18
'S' 0 10 155 25
'B' 1 7 104 18
'B' 0 3.5 147 19
'B' 1 8 110 25
'B' 0 10 108 25
'B' 0 5.5 113 25
'B' 0 6 115 24
'B' 0 6.5 61 19
'B' 1 6.5 60 26
'B' 1 8.5 109 10
'B' 1 4 68 17
'B' 1 9.5 111 13
'B' 0 8 77 17
'B' 0 8.5 73 30
'S' 1 5.5 151 25
'B' 0 7 89 4
'B' 0 9 78 16
'B' 0 8 110 21
'S' 0 10 220 23
'B' 1 8 65 22
'S' 1 6 141 17
'B' 0 8 117 20
'S' 0 5 122 20
'B' 1 9 63 22
'S' 0 4.5 44 16
'B' 1 8.5 52 23
'B' 1 9.5 131 0
'B' 0 8.5 101 18
'B' 1 7.5 42 25
'S' 1 7.5 152 23
'S' 1 5 107 12
'B' 0 7 77 18
'S' 0 8 154 24
'S' 0 5.5 103 11
'B' 1 8.5 96 18
'S' 0 9.5 175 23
'B' 1 7 57 24
'B' 1 8 112 29
'S' 0 8.5 143 18
'B' 0 3.5 49 15
'S' 0 6.5 110 29
'S' 1 6.5 131 16
'S' 1 10.5 167 19
'B' 0 8.5 56 22
'S' 0 8 137 16
'B' 0 10 86 23
'S' 1 10 121 23
'S' 1 9.5 149 19
'S' 0 9 168 4
'S' 0 10 140 20
'B' 0 7.5 88 24
'S' 1 4.5 168 20
'S' 1 4.5 94 4
'S' 1 0.5 51 24
'B' 1 6.5 48 22
'S' 0 4.5 145 16
'S' 1 5.5 66 3
'B' 1 5 85 15
'S' 1 6 109 24
'B' 0 4 63 17
'B' 0 8 102 20
'B' 1 10.5 162 27
'B' 1 6.5 86 26
'B' 1 8 114 23
'S' 1 8.5 164 17
'S' 0 5.5 119 20
'S' 1 7 126 22
'S' 0 5 132 19
'S' 1 3.5 142 24
'S' 1 5 83 19
'B' 0 9 94 23
'B' 1 8.5 81 15
'S' 0 5 166 27
'B' 1 9.5 110 26
'B' 0 3 64 22
'S' 1 1.5 93 22
'B' 0 6 104 18
'B' 0 0.5 105 15
'B' 1 6.5 49 22
'B' 1 7.5 88 27
'B' 0 4.5 95 10
'B' 1 8 102 20
'B' 1 9 99 17
'B' 0 7.5 63 23
'B' 1 8.5 76 19
'B' 0 7 109 13
'B' 0 9.5 117 27
'B' 1 6.5 57 23
'B' 1 9.5 120 16
'B' 0 6 73 25
'B' 1 8 91 2
'B' 0 9.5 108 26
'B' 0 8 105 20
'S' 1 8 117 23
'B' 0 9 119 22
'B' 0 5 31 24




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270618&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270618&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270618&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means20.319-0.84-0.210.667

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 20.319 & -0.84 & -0.21 & 0.667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270618&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]20.319[/C][C]-0.84[/C][C]-0.21[/C][C]0.667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270618&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270618&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
means20.319-0.84-0.210.667







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A113.38213.3820.5070.477
Treatment_B10.8350.8350.0320.859
Treatment_A:Treatment_B17.2977.2970.2760.6
Residuals2747235.48326.407

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 13.382 & 13.382 & 0.507 & 0.477 \tabularnewline
Treatment_B & 1 & 0.835 & 0.835 & 0.032 & 0.859 \tabularnewline
Treatment_A:Treatment_B & 1 & 7.297 & 7.297 & 0.276 & 0.6 \tabularnewline
Residuals & 274 & 7235.483 & 26.407 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270618&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]13.382[/C][C]13.382[/C][C]0.507[/C][C]0.477[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]0.835[/C][C]0.835[/C][C]0.032[/C][C]0.859[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]7.297[/C][C]7.297[/C][C]0.276[/C][C]0.6[/C][/ROW]
[ROW][C]Residuals[/C][C]274[/C][C]7235.483[/C][C]26.407[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270618&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270618&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_A113.38213.3820.5070.477
Treatment_B10.8350.8350.0320.859
Treatment_A:Treatment_B17.2977.2970.2760.6
Residuals2747235.48326.407







Tukey Honest Significant Difference Comparisons
difflwruprp adj
S-B-0.439-1.6530.7750.477
1-00.109-1.1161.3340.862
S:0-B:0-0.84-3.3151.6350.817
B:1-B:0-0.21-2.4922.0720.995
S:1-B:0-0.383-2.4641.6970.964
B:1-S:00.63-1.9063.1660.918
S:1-S:00.457-1.8992.8130.959
S:1-B:1-0.173-2.3261.9790.997

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
S-B & -0.439 & -1.653 & 0.775 & 0.477 \tabularnewline
1-0 & 0.109 & -1.116 & 1.334 & 0.862 \tabularnewline
S:0-B:0 & -0.84 & -3.315 & 1.635 & 0.817 \tabularnewline
B:1-B:0 & -0.21 & -2.492 & 2.072 & 0.995 \tabularnewline
S:1-B:0 & -0.383 & -2.464 & 1.697 & 0.964 \tabularnewline
B:1-S:0 & 0.63 & -1.906 & 3.166 & 0.918 \tabularnewline
S:1-S:0 & 0.457 & -1.899 & 2.813 & 0.959 \tabularnewline
S:1-B:1 & -0.173 & -2.326 & 1.979 & 0.997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270618&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]S-B[/C][C]-0.439[/C][C]-1.653[/C][C]0.775[/C][C]0.477[/C][/ROW]
[ROW][C]1-0[/C][C]0.109[/C][C]-1.116[/C][C]1.334[/C][C]0.862[/C][/ROW]
[ROW][C]S:0-B:0[/C][C]-0.84[/C][C]-3.315[/C][C]1.635[/C][C]0.817[/C][/ROW]
[ROW][C]B:1-B:0[/C][C]-0.21[/C][C]-2.492[/C][C]2.072[/C][C]0.995[/C][/ROW]
[ROW][C]S:1-B:0[/C][C]-0.383[/C][C]-2.464[/C][C]1.697[/C][C]0.964[/C][/ROW]
[ROW][C]B:1-S:0[/C][C]0.63[/C][C]-1.906[/C][C]3.166[/C][C]0.918[/C][/ROW]
[ROW][C]S:1-S:0[/C][C]0.457[/C][C]-1.899[/C][C]2.813[/C][C]0.959[/C][/ROW]
[ROW][C]S:1-B:1[/C][C]-0.173[/C][C]-2.326[/C][C]1.979[/C][C]0.997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270618&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270618&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
S-B-0.439-1.6530.7750.477
1-00.109-1.1161.3340.862
S:0-B:0-0.84-3.3151.6350.817
B:1-B:0-0.21-2.4922.0720.995
S:1-B:0-0.383-2.4641.6970.964
B:1-S:00.63-1.9063.1660.918
S:1-S:00.457-1.8992.8130.959
S:1-B:1-0.173-2.3261.9790.997







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.4470.72
274

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.447 & 0.72 \tabularnewline
  & 274 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270618&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]0.447[/C][C]0.72[/C][/ROW]
[ROW][C] [/C][C]274[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270618&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270618&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)
Group30.4470.72
274



Parameters (Session):
par1 = 5 ; par2 = 1 ; par3 = 2 ; par4 = TRUE ;
Parameters (R input):
par1 = 5 ; par2 = 1 ; par3 = 2 ; par4 = TRUE ;
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')