FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSat, 08 Dec 2012 08:20:57 -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/08/t13549728792qmtasc4ah9fv6s.htm/, Retrieved Fri, 19 Apr 2024 07:16:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197578, Retrieved Fri, 19 Apr 2024 07:16:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111

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] [] [2010-11-02 14:42:14] [b98453cac15ba1066b407e146608df68]
- R PD    [Two-Way ANOVA] [Paper] [2012-12-08 13:20:57] [38c0fff34b8aa23b45468de8b641bfee] [Current]
- R PD      [Two-Way ANOVA] [paper] [2012-12-15 16:16:16] [fa543719fe3f8358943b948de15add90]
- R PD      [Two-Way ANOVA] [paper] [2012-12-15 16:20:10] [fa543719fe3f8358943b948de15add90]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	0	'E'	0	1
0	1	'F'	1	0
0	0	'F'	0	1
0	0	'H'	0	1
0	0	'H'	0	1
0	0	'H'	0	1
0	1	'E'	1	1
0	1	'F'	1	1
0	0	'E'	0	1
0	1	'F'	1	0
0	0	'H'	0	0
0	0	'E'	0	0
0	1	'F'	1	1
0	0	'H'	0	0
0	1	'E'	1	0
0	0	'H'	0	0
0	0	'E'	0	1
0	0	'F'	0	1
0	0	'H'	0	0
0	1	'F'	1	0
0	0	'H'	0	0
0	0	'H'	0	1
0	0	'H'	0	0
0	0	'E'	0	0
0	1	'F'	1	0
0	1	'E'	1	0
0	1	'E'	1	0
1	1	'F'	0	1
0	0	'F'	0	0
0	0	'H'	0	0
0	0	'E'	0	1
0	1	'E'	1	1
0	0	'H'	0	1
0	1	'E'	1	1
0	1	'F'	1	1
0	0	'E'	0	1
0	1	'F'	1	0
0	0	'H'	0	0
0	1	'E'	1	0
0	1	'F'	1	0
0	1	'F'	1	0
0	0	'F'	0	0
0	1	'F'	1	0
0	1	'H'	1	1
0	1	'E'	1	0
0	0	'E'	0	0
0	0	'H'	0	0
0	1	'E'	1	1
0	0	'F'	0	1
0	0	'F'	0	0
0	0	'H'	0	0
0	0	'E'	0	1
0	1	'F'	1	1
0	1	'E'	1	1
0	0	'H'	0	1
0	0	'H'	0	1
0	0	'H'	0	1
0	0	'E'	0	1
0	0	'H'	0	0
0	1	'E'	1	0
0	0	'H'	0	1
0	0	'F'	0	1
0	0	'H'	0	1
0	1	'F'	1	0
0	0	'E'	0	1
0	1	'E'	1	1
0	0	'F'	0	0
0	0	'H'	0	1
0	0	'F'	0	0
0	0	'E'	0	1
1	0	'E'	-1	1
0	0	'H'	0	0
0	0	'H'	0	1
0	0	'F'	0	1
0	0	'H'	0	1
0	1	'E'	1	0
0	0	'F'	0	1
0	1	'E'	1	0
0	0	'E'	0	0
0	0	'E'	0	0
0	0	'F'	0	1
0	0	'E'	0	1
0	1	'F'	1	1
0	0	'H'	0	1
1	1	'H'	0	1
0	0	'H'	0	1
0	0	'F'	0	0
0	0	'H'	0	1
0	0	'H'	0	1
0	1	'F'	1	1
0	1	'F'	1	1
0	0	'H'	0	0
0	0	'F'	0	1
0	0	'H'	0	1
0	0	'E'	0	0
0	1	'F'	1	1
0	0	'E'	0	0
0	0	'H'	0	1
0	1	'F'	1	1
1	1	'F'	0	1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197578&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]3 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=197578&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197578&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.5330.067-0.533-0.2390.1130.287

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 0.533 & 0.067 & -0.533 & -0.239 & 0.113 & 0.287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197578&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]0.533[/C][C]0.067[/C][C]-0.533[/C][C]-0.239[/C][C]0.113[/C][C]0.287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197578&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197578&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
means0.5330.067-0.533-0.2390.1130.287






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A24.62.311.6540
Treatment_B20.2740.2741.3860.242
Treatment_A:Treatment_B20.3340.1670.8470.432
Residuals9418.5520.197 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 4.6 & 2.3 & 11.654 & 0 \tabularnewline
Treatment_B & 2 & 0.274 & 0.274 & 1.386 & 0.242 \tabularnewline
Treatment_A:Treatment_B & 2 & 0.334 & 0.167 & 0.847 & 0.432 \tabularnewline
Residuals & 94 & 18.552 & 0.197 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197578&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]4.6[/C][C]2.3[/C][C]11.654[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]0.274[/C][C]0.274[/C][C]1.386[/C][C]0.242[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]0.334[/C][C]0.167[/C][C]0.847[/C][C]0.432[/C][/ROW]
[ROW][C]Residuals[/C][C]94[/C][C]18.552[/C][C]0.197[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197578&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197578&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)
2
Treatment_A24.62.311.6540
Treatment_B20.2740.2741.3860.242
Treatment_A:Treatment_B20.3340.1670.8470.432
Residuals9418.5520.197






Tukey Honest Significant Difference Comparisons
difflwruprp adj
F-E0.123-0.1370.3840.501
H-E-0.377-0.637-0.1160.002
H-F-0.5-0.757-0.2430
1-0-0.105-0.2840.0730.243
F:0-E:00.067-0.4050.5390.998
H:0-E:0-0.533-1.023-0.0440.025
E:1-E:0-0.239-0.6970.2190.652
F:1-E:0-0.06-0.5060.3870.999
H:1-E:0-0.486-0.923-0.0490.02
H:0-F:0-0.6-1.09-0.110.007
E:1-F:0-0.306-0.7640.1520.383
F:1-F:0-0.126-0.5730.320.963
H:1-F:0-0.552-0.989-0.1150.005
E:1-H:00.294-0.1820.770.473
F:1-H:00.4740.0080.9390.043
H:1-H:00.048-0.4090.5041
F:1-E:10.18-0.2520.6110.831
H:1-E:1-0.246-0.6680.1750.535
H:1-F:1-0.426-0.835-0.0170.036

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
F-E & 0.123 & -0.137 & 0.384 & 0.501 \tabularnewline
H-E & -0.377 & -0.637 & -0.116 & 0.002 \tabularnewline
H-F & -0.5 & -0.757 & -0.243 & 0 \tabularnewline
1-0 & -0.105 & -0.284 & 0.073 & 0.243 \tabularnewline
F:0-E:0 & 0.067 & -0.405 & 0.539 & 0.998 \tabularnewline
H:0-E:0 & -0.533 & -1.023 & -0.044 & 0.025 \tabularnewline
E:1-E:0 & -0.239 & -0.697 & 0.219 & 0.652 \tabularnewline
F:1-E:0 & -0.06 & -0.506 & 0.387 & 0.999 \tabularnewline
H:1-E:0 & -0.486 & -0.923 & -0.049 & 0.02 \tabularnewline
H:0-F:0 & -0.6 & -1.09 & -0.11 & 0.007 \tabularnewline
E:1-F:0 & -0.306 & -0.764 & 0.152 & 0.383 \tabularnewline
F:1-F:0 & -0.126 & -0.573 & 0.32 & 0.963 \tabularnewline
H:1-F:0 & -0.552 & -0.989 & -0.115 & 0.005 \tabularnewline
E:1-H:0 & 0.294 & -0.182 & 0.77 & 0.473 \tabularnewline
F:1-H:0 & 0.474 & 0.008 & 0.939 & 0.043 \tabularnewline
H:1-H:0 & 0.048 & -0.409 & 0.504 & 1 \tabularnewline
F:1-E:1 & 0.18 & -0.252 & 0.611 & 0.831 \tabularnewline
H:1-E:1 & -0.246 & -0.668 & 0.175 & 0.535 \tabularnewline
H:1-F:1 & -0.426 & -0.835 & -0.017 & 0.036 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197578&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]F-E[/C][C]0.123[/C][C]-0.137[/C][C]0.384[/C][C]0.501[/C][/ROW]
[ROW][C]H-E[/C][C]-0.377[/C][C]-0.637[/C][C]-0.116[/C][C]0.002[/C][/ROW]
[ROW][C]H-F[/C][C]-0.5[/C][C]-0.757[/C][C]-0.243[/C][C]0[/C][/ROW]
[ROW][C]1-0[/C][C]-0.105[/C][C]-0.284[/C][C]0.073[/C][C]0.243[/C][/ROW]
[ROW][C]F:0-E:0[/C][C]0.067[/C][C]-0.405[/C][C]0.539[/C][C]0.998[/C][/ROW]
[ROW][C]H:0-E:0[/C][C]-0.533[/C][C]-1.023[/C][C]-0.044[/C][C]0.025[/C][/ROW]
[ROW][C]E:1-E:0[/C][C]-0.239[/C][C]-0.697[/C][C]0.219[/C][C]0.652[/C][/ROW]
[ROW][C]F:1-E:0[/C][C]-0.06[/C][C]-0.506[/C][C]0.387[/C][C]0.999[/C][/ROW]
[ROW][C]H:1-E:0[/C][C]-0.486[/C][C]-0.923[/C][C]-0.049[/C][C]0.02[/C][/ROW]
[ROW][C]H:0-F:0[/C][C]-0.6[/C][C]-1.09[/C][C]-0.11[/C][C]0.007[/C][/ROW]
[ROW][C]E:1-F:0[/C][C]-0.306[/C][C]-0.764[/C][C]0.152[/C][C]0.383[/C][/ROW]
[ROW][C]F:1-F:0[/C][C]-0.126[/C][C]-0.573[/C][C]0.32[/C][C]0.963[/C][/ROW]
[ROW][C]H:1-F:0[/C][C]-0.552[/C][C]-0.989[/C][C]-0.115[/C][C]0.005[/C][/ROW]
[ROW][C]E:1-H:0[/C][C]0.294[/C][C]-0.182[/C][C]0.77[/C][C]0.473[/C][/ROW]
[ROW][C]F:1-H:0[/C][C]0.474[/C][C]0.008[/C][C]0.939[/C][C]0.043[/C][/ROW]
[ROW][C]H:1-H:0[/C][C]0.048[/C][C]-0.409[/C][C]0.504[/C][C]1[/C][/ROW]
[ROW][C]F:1-E:1[/C][C]0.18[/C][C]-0.252[/C][C]0.611[/C][C]0.831[/C][/ROW]
[ROW][C]H:1-E:1[/C][C]-0.246[/C][C]-0.668[/C][C]0.175[/C][C]0.535[/C][/ROW]
[ROW][C]H:1-F:1[/C][C]-0.426[/C][C]-0.835[/C][C]-0.017[/C][C]0.036[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197578&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197578&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:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
F-E0.123-0.1370.3840.501
H-E-0.377-0.637-0.1160.002
H-F-0.5-0.757-0.2430
1-0-0.105-0.2840.0730.243
F:0-E:00.067-0.4050.5390.998
H:0-E:0-0.533-1.023-0.0440.025
E:1-E:0-0.239-0.6970.2190.652
F:1-E:0-0.06-0.5060.3870.999
H:1-E:0-0.486-0.923-0.0490.02
H:0-F:0-0.6-1.09-0.110.007
E:1-F:0-0.306-0.7640.1520.383
F:1-F:0-0.126-0.5730.320.963
H:1-F:0-0.552-0.989-0.1150.005
E:1-H:00.294-0.1820.770.473
F:1-H:00.4740.0080.9390.043
H:1-H:00.048-0.4090.5041
F:1-E:10.18-0.2520.6110.831
H:1-E:1-0.246-0.6680.1750.535
H:1-F:1-0.426-0.835-0.0170.036






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group54.2340.002
94 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 4.234 & 0.002 \tabularnewline
  & 94 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197578&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]5[/C][C]4.234[/C][C]0.002[/C][/ROW]
[ROW][C] [/C][C]94[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197578&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197578&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)
Group54.2340.002
94


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = 3 ; par3 = 5 ; par4 = TRUE ;
Parameters (R input):
par1 = 4 ; par2 = 3 ; par3 = 5 ; par4 = TRUE ;
R code (references can be found in the software module):
par4 <- 'TRUE'
par3 <- '5'
par2 <- '3'
par1 <- '4'
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')