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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 computationSat, 11 Dec 2010 19:16:51 +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/2010/Dec/11/t1292094917kxxvs1crod7jsii.htm/, Retrieved Mon, 06 May 2024 17:19:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108288, Retrieved Mon, 06 May 2024 17:19:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
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]
-   PD    [Two-Way ANOVA] [Two-Way ANOVA: Po...] [2010-12-11 19:16:51] [bff44ea937c3f909b1dc9a8bfab919e2] [Current]
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Dataseries X:
13	'LO'	2
12	'LO'	1
15	'LO'	1
12	'AV'	1
10	'AV'	2
12	'LO'	2
15	'AV'	1
9	'LO'	1
12	'AV'	1
11	'LO'	1
11	'AV'	2
11	'LO'	1
15	'AV'	1
7	'AV'	2
11	'LO'	2
11	'LO'	1
10	'LO'	1
14	'AV'	2
10	'LO'	1
6	'LO'	2
11	'LO'	1
15	'AV'	2
11	'AV'	1
12	'LO'	2
14	'LO'	1
15	'LO'	2
9	'LO'	2
13	'AV'	1
13	'LO'	2
16	'AV'	1
13	'AV'	1
12	'AV'	2
14	'AV'	1
11	'LO'	2
9	'LO'	1
16	'AV'	2
12	'AV'	1
10	'AV'	2
13	'LO'	1
16	'AV'	1
14	'AV'	2
15	'LO'	1
5	'LO'	1
8	'LO'	2
11	'LO'	1
16	'AV'	2
17	'HI'	1
9	'LO'	2
9	'LO'	1
13	'LO'	1
10	'LO'	1
6	'AV'	2
12	'LO'	2
8	'LO'	2
14	'LO'	2
12	'AV'	1
11	'LO'	1
16	'AV'	1
8	'AV'	2
15	'LO'	1
7	'LO'	2
16	'AV'	2
14	'LO'	1
16	'LO'	1
9	'AV'	1
14	'LO'	1
11	'AV'	2
13	'LO'	2
15	'AV'	1
5	'LO'	2
15	'AV'	1
13	'AV'	1
11	'AV'	2
11	'AV'	2
12	'AV'	1
12	'AV'	1
12	'AV'	1
12	'AV'	1
14	'LO'	1
6	'LO'	1
7	'LO'	2
14	'AV'	1
14	'AV'	1
10	'LO'	1
13	'AV'	2
12	'LO'	2
9	'LO'	2
12	'LO'	1
16	'LO'	1
10	'AV'	2
14	'LO'	1
10	'AV'	1
16	'AV'	1
15	'AV'	1
12	'AV'	2
10	'LO'	1
8	'LO'	1
8	'LO'	2
11	'LO'	2
13	'AV'	1
16	'AV'	1
16	'AV'	1
14	'LO'	2
11	'LO'	1
4	'LO'	2
14	'AV'	1
9	'AV'	1
14	'AV'	1
8	'LO'	1
8	'LO'	1
11	'LO'	1
12	'LO'	1
11	'LO'	1
14	'LO'	1
15	'AV'	2
16	'AV'	1
16	'LO'	1
11	'LO'	2
14	'AV'	2
14	'LO'	2
12	'AV'	1
14	'AV'	2
8	'AV'	2
13	'AV'	2
16	'AV'	2
12	'LO'	1
16	'AV'	1
12	'LO'	1
11	'LO'	1
4	'LO'	1
16	'HI'	1
15	'AV'	1
10	'LO'	1
13	'HI'	1
15	'LO'	2
12	'LO'	1
14	'AV'	2
7	'LO'	1
19	'LO'	1
12	'AV'	1
12	'LO'	2
13	'LO'	2
15	'LO'	1
8	'AV'	2
12	'LO'	1
10	'LO'	1
8	'LO'	2
10	'AV'	2
15	'AV'	2
16	'LO'	1
13	'AV'	1
16	'AV'	1
9	'LO'	1
14	'LO'	2
14	'AV'	2
12	'LO'	1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108288&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108288&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108288&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'George Udny Yule' @ 72.249.76.132







ANOVA Model
Response ~ Treatment_A * Treatment_B
means13.5381.795-2.01-1.405NA0.522

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 13.538 & 1.795 & -2.01 & -1.405 & NA & 0.522 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108288&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]13.538[/C][C]1.795[/C][C]-2.01[/C][C]-1.405[/C][C]NA[/C][C]0.522[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108288&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108288&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
means13.5381.795-2.01-1.405NA0.522







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A2145.82272.9119.640
Treatment_B246.25946.2596.1160.015
Treatment_A:Treatment_B22.4752.4750.3270.568
Residuals1511142.137.564

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 145.822 & 72.911 & 9.64 & 0 \tabularnewline
Treatment_B & 2 & 46.259 & 46.259 & 6.116 & 0.015 \tabularnewline
Treatment_A:Treatment_B & 2 & 2.475 & 2.475 & 0.327 & 0.568 \tabularnewline
Residuals & 151 & 1142.13 & 7.564 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108288&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]2[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Treatment_A[/C][C]2[/C][C]145.822[/C][C]72.911[/C][C]9.64[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]46.259[/C][C]46.259[/C][C]6.116[/C][C]0.015[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]2.475[/C][C]2.475[/C][C]0.327[/C][C]0.568[/C][/ROW]
[ROW][C]Residuals[/C][C]151[/C][C]1142.13[/C][C]7.564[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108288&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108288&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)
2
Treatment_A2145.82272.9119.640
Treatment_B246.25946.2596.1160.015
Treatment_A:Treatment_B22.4752.4750.3270.568
Residuals1511142.137.564







Tukey Honest Significant Difference Comparisons
difflwruprp adj
HI-AV2.406-1.4346.2450.302
LO-AV-1.725-2.783-0.6670
LO-HI-4.131-7.956-0.3060.031
2-1-1.106-1.998-0.2150.015
HI:1-AV:11.795-2.9626.5510.885
LO:1-AV:1-2.01-3.685-0.3350.009
AV:2-AV:1-1.405-3.3330.5230.291
HI:2-AV:1NANANANA
LO:2-AV:1-2.893-4.804-0.9830
LO:1-HI:1-3.805-8.5170.9060.188
AV:2-HI:1-3.2-8.0071.6070.393
HI:2-HI:1NANANANA
LO:2-HI:1-4.688-9.4880.1120.06
AV:2-LO:10.605-1.2092.4190.929
HI:2-LO:1NANANANA
LO:2-LO:1-0.883-2.6780.9120.715
HI:2-AV:2NANANANA
LO:2-AV:2-1.488-3.5210.5450.286
LO:2-HI:2NANANANA

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
HI-AV & 2.406 & -1.434 & 6.245 & 0.302 \tabularnewline
LO-AV & -1.725 & -2.783 & -0.667 & 0 \tabularnewline
LO-HI & -4.131 & -7.956 & -0.306 & 0.031 \tabularnewline
2-1 & -1.106 & -1.998 & -0.215 & 0.015 \tabularnewline
HI:1-AV:1 & 1.795 & -2.962 & 6.551 & 0.885 \tabularnewline
LO:1-AV:1 & -2.01 & -3.685 & -0.335 & 0.009 \tabularnewline
AV:2-AV:1 & -1.405 & -3.333 & 0.523 & 0.291 \tabularnewline
HI:2-AV:1 & NA & NA & NA & NA \tabularnewline
LO:2-AV:1 & -2.893 & -4.804 & -0.983 & 0 \tabularnewline
LO:1-HI:1 & -3.805 & -8.517 & 0.906 & 0.188 \tabularnewline
AV:2-HI:1 & -3.2 & -8.007 & 1.607 & 0.393 \tabularnewline
HI:2-HI:1 & NA & NA & NA & NA \tabularnewline
LO:2-HI:1 & -4.688 & -9.488 & 0.112 & 0.06 \tabularnewline
AV:2-LO:1 & 0.605 & -1.209 & 2.419 & 0.929 \tabularnewline
HI:2-LO:1 & NA & NA & NA & NA \tabularnewline
LO:2-LO:1 & -0.883 & -2.678 & 0.912 & 0.715 \tabularnewline
HI:2-AV:2 & NA & NA & NA & NA \tabularnewline
LO:2-AV:2 & -1.488 & -3.521 & 0.545 & 0.286 \tabularnewline
LO:2-HI:2 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108288&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]HI-AV[/C][C]2.406[/C][C]-1.434[/C][C]6.245[/C][C]0.302[/C][/ROW]
[ROW][C]LO-AV[/C][C]-1.725[/C][C]-2.783[/C][C]-0.667[/C][C]0[/C][/ROW]
[ROW][C]LO-HI[/C][C]-4.131[/C][C]-7.956[/C][C]-0.306[/C][C]0.031[/C][/ROW]
[ROW][C]2-1[/C][C]-1.106[/C][C]-1.998[/C][C]-0.215[/C][C]0.015[/C][/ROW]
[ROW][C]HI:1-AV:1[/C][C]1.795[/C][C]-2.962[/C][C]6.551[/C][C]0.885[/C][/ROW]
[ROW][C]LO:1-AV:1[/C][C]-2.01[/C][C]-3.685[/C][C]-0.335[/C][C]0.009[/C][/ROW]
[ROW][C]AV:2-AV:1[/C][C]-1.405[/C][C]-3.333[/C][C]0.523[/C][C]0.291[/C][/ROW]
[ROW][C]HI:2-AV:1[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]LO:2-AV:1[/C][C]-2.893[/C][C]-4.804[/C][C]-0.983[/C][C]0[/C][/ROW]
[ROW][C]LO:1-HI:1[/C][C]-3.805[/C][C]-8.517[/C][C]0.906[/C][C]0.188[/C][/ROW]
[ROW][C]AV:2-HI:1[/C][C]-3.2[/C][C]-8.007[/C][C]1.607[/C][C]0.393[/C][/ROW]
[ROW][C]HI:2-HI:1[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]LO:2-HI:1[/C][C]-4.688[/C][C]-9.488[/C][C]0.112[/C][C]0.06[/C][/ROW]
[ROW][C]AV:2-LO:1[/C][C]0.605[/C][C]-1.209[/C][C]2.419[/C][C]0.929[/C][/ROW]
[ROW][C]HI:2-LO:1[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]LO:2-LO:1[/C][C]-0.883[/C][C]-2.678[/C][C]0.912[/C][C]0.715[/C][/ROW]
[ROW][C]HI:2-AV:2[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]LO:2-AV:2[/C][C]-1.488[/C][C]-3.521[/C][C]0.545[/C][C]0.286[/C][/ROW]
[ROW][C]LO:2-HI:2[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108288&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108288&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
HI-AV2.406-1.4346.2450.302
LO-AV-1.725-2.783-0.6670
LO-HI-4.131-7.956-0.3060.031
2-1-1.106-1.998-0.2150.015
HI:1-AV:11.795-2.9626.5510.885
LO:1-AV:1-2.01-3.685-0.3350.009
AV:2-AV:1-1.405-3.3330.5230.291
HI:2-AV:1NANANANA
LO:2-AV:1-2.893-4.804-0.9830
LO:1-HI:1-3.805-8.5170.9060.188
AV:2-HI:1-3.2-8.0071.6070.393
HI:2-HI:1NANANANA
LO:2-HI:1-4.688-9.4880.1120.06
AV:2-LO:10.605-1.2092.4190.929
HI:2-LO:1NANANANA
LO:2-LO:1-0.883-2.6780.9120.715
HI:2-AV:2NANANANA
LO:2-AV:2-1.488-3.5210.5450.286
LO:2-HI:2NANANANA







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group41.5690.185
151

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 1.569 & 0.185 \tabularnewline
  & 151 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108288&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]4[/C][C]1.569[/C][C]0.185[/C][/ROW]
[ROW][C] [/C][C]151[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108288&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108288&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)
Group41.5690.185
151



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 3 ; 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')