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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 computationTue, 08 Nov 2011 20:34:19 -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/2011/Nov/08/t1320802480g5us69ck3dojqpo.htm/, Retrieved Thu, 18 Apr 2024 16:09:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=141066, Retrieved Thu, 18 Apr 2024 16:09:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97

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] [Workshop 5, quest...] [2010-11-01 20:51:26] [3635fb7041b1998c5a1332cf9de22bce]
-   P     [Two-Way ANOVA] [Workshop 5 Questi...] [2011-11-09 01:34:19] [635499bc27d9f41bf7bccae25a54e146] [Current]
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Dataset

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

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'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141066&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141066&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141066&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'AstonUniversity' @ aston.wessa.net






ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.30.178-0.2620.171-0.119-0.209

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 0.3 & 0.178 & -0.262 & 0.171 & -0.119 & -0.209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141066&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]0.3[/C][C]0.178[/C][C]-0.262[/C][C]0.171[/C][C]-0.119[/C][C]-0.209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141066&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141066&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
means0.30.178-0.2620.171-0.119-0.209






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A24.8522.42612.6010
Treatment_B20.1050.1050.5460.462
Treatment_A:Treatment_B20.2010.1010.5230.594
Residuals11121.3710.193 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 4.852 & 2.426 & 12.601 & 0 \tabularnewline
Treatment_B & 2 & 0.105 & 0.105 & 0.546 & 0.462 \tabularnewline
Treatment_A:Treatment_B & 2 & 0.201 & 0.101 & 0.523 & 0.594 \tabularnewline
Residuals & 111 & 21.371 & 0.193 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141066&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]4.852[/C][C]2.426[/C][C]12.601[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]0.105[/C][C]0.105[/C][C]0.546[/C][C]0.462[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]0.201[/C][C]0.101[/C][C]0.523[/C][C]0.594[/C][/ROW]
[ROW][C]Residuals[/C][C]111[/C][C]21.371[/C][C]0.193[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141066&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141066&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_A24.8522.42612.6010
Treatment_B20.1050.1050.5460.462
Treatment_A:Treatment_B20.2010.1010.5230.594
Residuals11121.3710.193






Tukey Honest Significant Difference Comparisons
difflwruprp adj
F-E0.122-0.1160.3590.447
H-E-0.353-0.591-0.1160.002
H-F-0.475-0.708-0.2420
V-M0.061-0.1030.2240.463
F:M-E:M0.178-0.2110.5670.768
H:M-E:M-0.262-0.640.1170.347
E:V-E:M0.171-0.2490.590.846
F:V-E:M0.229-0.190.6490.61
H:V-E:M-0.3-0.7430.1430.371
H:M-F:M-0.44-0.804-0.0760.009
E:V-F:M-0.008-0.4150.3991
F:V-F:M0.051-0.3560.4580.999
H:V-F:M-0.478-0.91-0.0470.021
E:V-H:M0.4320.0350.8290.024
F:V-H:M0.4910.0940.8880.006
H:V-H:M-0.038-0.460.3831
F:V-E:V0.059-0.3780.4950.999
H:V-E:V-0.471-0.93-0.0110.041
H:V-F:V-0.529-0.989-0.070.014

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
F-E & 0.122 & -0.116 & 0.359 & 0.447 \tabularnewline
H-E & -0.353 & -0.591 & -0.116 & 0.002 \tabularnewline
H-F & -0.475 & -0.708 & -0.242 & 0 \tabularnewline
V-M & 0.061 & -0.103 & 0.224 & 0.463 \tabularnewline
F:M-E:M & 0.178 & -0.211 & 0.567 & 0.768 \tabularnewline
H:M-E:M & -0.262 & -0.64 & 0.117 & 0.347 \tabularnewline
E:V-E:M & 0.171 & -0.249 & 0.59 & 0.846 \tabularnewline
F:V-E:M & 0.229 & -0.19 & 0.649 & 0.61 \tabularnewline
H:V-E:M & -0.3 & -0.743 & 0.143 & 0.371 \tabularnewline
H:M-F:M & -0.44 & -0.804 & -0.076 & 0.009 \tabularnewline
E:V-F:M & -0.008 & -0.415 & 0.399 & 1 \tabularnewline
F:V-F:M & 0.051 & -0.356 & 0.458 & 0.999 \tabularnewline
H:V-F:M & -0.478 & -0.91 & -0.047 & 0.021 \tabularnewline
E:V-H:M & 0.432 & 0.035 & 0.829 & 0.024 \tabularnewline
F:V-H:M & 0.491 & 0.094 & 0.888 & 0.006 \tabularnewline
H:V-H:M & -0.038 & -0.46 & 0.383 & 1 \tabularnewline
F:V-E:V & 0.059 & -0.378 & 0.495 & 0.999 \tabularnewline
H:V-E:V & -0.471 & -0.93 & -0.011 & 0.041 \tabularnewline
H:V-F:V & -0.529 & -0.989 & -0.07 & 0.014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141066&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]0.122[/C][C]-0.116[/C][C]0.359[/C][C]0.447[/C][/ROW]
[ROW][C]H-E[/C][C]-0.353[/C][C]-0.591[/C][C]-0.116[/C][C]0.002[/C][/ROW]
[ROW][C]H-F[/C][C]-0.475[/C][C]-0.708[/C][C]-0.242[/C][C]0[/C][/ROW]
[ROW][C]V-M[/C][C]0.061[/C][C]-0.103[/C][C]0.224[/C][C]0.463[/C][/ROW]
[ROW][C]F:M-E:M[/C][C]0.178[/C][C]-0.211[/C][C]0.567[/C][C]0.768[/C][/ROW]
[ROW][C]H:M-E:M[/C][C]-0.262[/C][C]-0.64[/C][C]0.117[/C][C]0.347[/C][/ROW]
[ROW][C]E:V-E:M[/C][C]0.171[/C][C]-0.249[/C][C]0.59[/C][C]0.846[/C][/ROW]
[ROW][C]F:V-E:M[/C][C]0.229[/C][C]-0.19[/C][C]0.649[/C][C]0.61[/C][/ROW]
[ROW][C]H:V-E:M[/C][C]-0.3[/C][C]-0.743[/C][C]0.143[/C][C]0.371[/C][/ROW]
[ROW][C]H:M-F:M[/C][C]-0.44[/C][C]-0.804[/C][C]-0.076[/C][C]0.009[/C][/ROW]
[ROW][C]E:V-F:M[/C][C]-0.008[/C][C]-0.415[/C][C]0.399[/C][C]1[/C][/ROW]
[ROW][C]F:V-F:M[/C][C]0.051[/C][C]-0.356[/C][C]0.458[/C][C]0.999[/C][/ROW]
[ROW][C]H:V-F:M[/C][C]-0.478[/C][C]-0.91[/C][C]-0.047[/C][C]0.021[/C][/ROW]
[ROW][C]E:V-H:M[/C][C]0.432[/C][C]0.035[/C][C]0.829[/C][C]0.024[/C][/ROW]
[ROW][C]F:V-H:M[/C][C]0.491[/C][C]0.094[/C][C]0.888[/C][C]0.006[/C][/ROW]
[ROW][C]H:V-H:M[/C][C]-0.038[/C][C]-0.46[/C][C]0.383[/C][C]1[/C][/ROW]
[ROW][C]F:V-E:V[/C][C]0.059[/C][C]-0.378[/C][C]0.495[/C][C]0.999[/C][/ROW]
[ROW][C]H:V-E:V[/C][C]-0.471[/C][C]-0.93[/C][C]-0.011[/C][C]0.041[/C][/ROW]
[ROW][C]H:V-F:V[/C][C]-0.529[/C][C]-0.989[/C][C]-0.07[/C][C]0.014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141066&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141066&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-E0.122-0.1160.3590.447
H-E-0.353-0.591-0.1160.002
H-F-0.475-0.708-0.2420
V-M0.061-0.1030.2240.463
F:M-E:M0.178-0.2110.5670.768
H:M-E:M-0.262-0.640.1170.347
E:V-E:M0.171-0.2490.590.846
F:V-E:M0.229-0.190.6490.61
H:V-E:M-0.3-0.7430.1430.371
H:M-F:M-0.44-0.804-0.0760.009
E:V-F:M-0.008-0.4150.3991
F:V-F:M0.051-0.3560.4580.999
H:V-F:M-0.478-0.91-0.0470.021
E:V-H:M0.4320.0350.8290.024
F:V-H:M0.4910.0940.8880.006
H:V-H:M-0.038-0.460.3831
F:V-E:V0.059-0.3780.4950.999
H:V-E:V-0.471-0.93-0.0110.041
H:V-F:V-0.529-0.989-0.070.014






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group55.5040
111 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 5.504 & 0 \tabularnewline
  & 111 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=141066&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]5.504[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]111[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=141066&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=141066&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)
Group55.5040
111


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 0.95 ; par4 = two.sided ; par5 = paired ; par6 = 0.0 ;
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')