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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, 02 Nov 2010 13:33:25 +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/Nov/02/t1288704720zz92kpjrtx44drr.htm/, Retrieved Sat, 27 Apr 2024 23:54:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=91423, Retrieved Sat, 27 Apr 2024 23:54:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact169

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] [Golfballs] [2010-10-25 12:43:22] [b98453cac15ba1066b407e146608df68]
-   PD  [Two-Way ANOVA] [WS5: Vraag 8] [2010-10-29 09:31:50] [1fd136673b2a4fecb5c545b9b4a05d64]
-   PD      [Two-Way ANOVA] [question 8] [2010-11-02 13:33:25] [4f70e6cd0867f10d298e58e8e27859b5] [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'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91423&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91423&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91423&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






ANOVA Model
Response ~ Treatment_A * Treatment_B
means0.30.2-0.2620.171-0.141-0.209

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 0.3 & 0.2 & -0.262 & 0.171 & -0.141 & -0.209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91423&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]0.2[/C][C]-0.262[/C][C]0.171[/C][C]-0.141[/C][C]-0.209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91423&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91423&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
means0.30.2-0.2620.171-0.141-0.209






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A25.0182.50913.0610
Treatment_B20.0810.0810.420.518
Treatment_A:Treatment_B20.2090.1040.5430.583
Residuals11021.1320.192 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 5.018 & 2.509 & 13.061 & 0 \tabularnewline
Treatment_B & 2 & 0.081 & 0.081 & 0.42 & 0.518 \tabularnewline
Treatment_A:Treatment_B & 2 & 0.209 & 0.104 & 0.543 & 0.583 \tabularnewline
Residuals & 110 & 21.132 & 0.192 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91423&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]5.018[/C][C]2.509[/C][C]13.061[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]0.081[/C][C]0.081[/C][C]0.42[/C][C]0.518[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]0.209[/C][C]0.104[/C][C]0.543[/C][C]0.583[/C][/ROW]
[ROW][C]Residuals[/C][C]110[/C][C]21.132[/C][C]0.192[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91423&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91423&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_A25.0182.50913.0610
Treatment_B20.0810.0810.420.518
Treatment_A:Treatment_B20.2090.1040.5430.583
Residuals11021.1320.192






Tukey Honest Significant Difference Comparisons
difflwruprp adj
F-E0.134-0.1050.3730.378
H-E-0.353-0.591-0.1160.002
H-F-0.488-0.722-0.2530
V-M0.053-0.110.2170.52
F:M-E:M0.2-0.1930.5930.68
H:M-E:M-0.262-0.640.1170.346
E:V-E:M0.171-0.2490.590.846
F:V-E:M0.229-0.190.6490.609
H:V-E:M-0.3-0.7430.1430.37
H:M-F:M-0.462-0.83-0.0930.006
E:V-F:M-0.029-0.440.3811
F:V-F:M0.029-0.3810.441
H:V-F:M-0.5-0.935-0.0650.014
E:V-H:M0.4320.0360.8290.024
F:V-H:M0.4910.0940.8870.006
H:V-H:M-0.038-0.460.3831
F:V-E:V0.059-0.3770.4950.999
H:V-E:V-0.471-0.929-0.0120.041
H:V-F:V-0.529-0.988-0.0710.014

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
F-E & 0.134 & -0.105 & 0.373 & 0.378 \tabularnewline
H-E & -0.353 & -0.591 & -0.116 & 0.002 \tabularnewline
H-F & -0.488 & -0.722 & -0.253 & 0 \tabularnewline
V-M & 0.053 & -0.11 & 0.217 & 0.52 \tabularnewline
F:M-E:M & 0.2 & -0.193 & 0.593 & 0.68 \tabularnewline
H:M-E:M & -0.262 & -0.64 & 0.117 & 0.346 \tabularnewline
E:V-E:M & 0.171 & -0.249 & 0.59 & 0.846 \tabularnewline
F:V-E:M & 0.229 & -0.19 & 0.649 & 0.609 \tabularnewline
H:V-E:M & -0.3 & -0.743 & 0.143 & 0.37 \tabularnewline
H:M-F:M & -0.462 & -0.83 & -0.093 & 0.006 \tabularnewline
E:V-F:M & -0.029 & -0.44 & 0.381 & 1 \tabularnewline
F:V-F:M & 0.029 & -0.381 & 0.44 & 1 \tabularnewline
H:V-F:M & -0.5 & -0.935 & -0.065 & 0.014 \tabularnewline
E:V-H:M & 0.432 & 0.036 & 0.829 & 0.024 \tabularnewline
F:V-H:M & 0.491 & 0.094 & 0.887 & 0.006 \tabularnewline
H:V-H:M & -0.038 & -0.46 & 0.383 & 1 \tabularnewline
F:V-E:V & 0.059 & -0.377 & 0.495 & 0.999 \tabularnewline
H:V-E:V & -0.471 & -0.929 & -0.012 & 0.041 \tabularnewline
H:V-F:V & -0.529 & -0.988 & -0.071 & 0.014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91423&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]0.134[/C][C]-0.105[/C][C]0.373[/C][C]0.378[/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]-0.488[/C][C]-0.722[/C][C]-0.253[/C][C]0[/C][/ROW]
[ROW][C]V-M[/C][C]0.053[/C][C]-0.11[/C][C]0.217[/C][C]0.52[/C][/ROW]
[ROW][C]F:M-E:M[/C][C]0.2[/C][C]-0.193[/C][C]0.593[/C][C]0.68[/C][/ROW]
[ROW][C]H:M-E:M[/C][C]-0.262[/C][C]-0.64[/C][C]0.117[/C][C]0.346[/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]0.609[/C][/ROW]
[ROW][C]H:V-E:M[/C][C]-0.3[/C][C]-0.743[/C][C]0.143[/C][C]0.37[/C][/ROW]
[ROW][C]H:M-F:M[/C][C]-0.462[/C][C]-0.83[/C][C]-0.093[/C][C]0.006[/C][/ROW]
[ROW][C]E:V-F:M[/C][C]-0.029[/C][C]-0.44[/C][C]0.381[/C][C]1[/C][/ROW]
[ROW][C]F:V-F:M[/C][C]0.029[/C][C]-0.381[/C][C]0.44[/C][C]1[/C][/ROW]
[ROW][C]H:V-F:M[/C][C]-0.5[/C][C]-0.935[/C][C]-0.065[/C][C]0.014[/C][/ROW]
[ROW][C]E:V-H:M[/C][C]0.432[/C][C]0.036[/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]0.887[/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]-0.377[/C][C]0.495[/C][C]0.999[/C][/ROW]
[ROW][C]H:V-E:V[/C][C]-0.471[/C][C]-0.929[/C][C]-0.012[/C][C]0.041[/C][/ROW]
[ROW][C]H:V-F:V[/C][C]-0.529[/C][C]-0.988[/C][C]-0.071[/C][C]0.014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91423&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91423&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-E0.134-0.1050.3730.378
H-E-0.353-0.591-0.1160.002
H-F-0.488-0.722-0.2530
V-M0.053-0.110.2170.52
F:M-E:M0.2-0.1930.5930.68
H:M-E:M-0.262-0.640.1170.346
E:V-E:M0.171-0.2490.590.846
F:V-E:M0.229-0.190.6490.609
H:V-E:M-0.3-0.7430.1430.37
H:M-F:M-0.462-0.83-0.0930.006
E:V-F:M-0.029-0.440.3811
F:V-F:M0.029-0.3810.441
H:V-F:M-0.5-0.935-0.0650.014
E:V-H:M0.4320.0360.8290.024
F:V-H:M0.4910.0940.8870.006
H:V-H:M-0.038-0.460.3831
F:V-E:V0.059-0.3770.4950.999
H:V-E:V-0.471-0.929-0.0120.041
H:V-F:V-0.529-0.988-0.0710.014






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group57.8770
110 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 7.877 & 0 \tabularnewline
  & 110 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91423&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]7.877[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]110[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91423&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91423&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)
Group57.8770
110


Figures (Output of Computation)

Input Parameters & R Code

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