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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 computationMon, 29 Oct 2012 12:07:27 -0400
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/Oct/29/t13515268776moc4pbqm21d2sp.htm/, Retrieved Sat, 27 Apr 2024 08:43:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=184641, Retrieved Sat, 27 Apr 2024 08:43:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2012-10-26 09:39:55] [7722d8427d2b2c713c1f0d5525f2f86c]
- R  D  [Paired and Unpaired Two Samples Tests about the Mean] [ws5] [2012-10-26 09:54:54] [7722d8427d2b2c713c1f0d5525f2f86c]
- R  D    [Paired and Unpaired Two Samples Tests about the Mean] [ws5] [2012-10-26 11:26:46] [7722d8427d2b2c713c1f0d5525f2f86c]
- R  D      [Paired and Unpaired Two Samples Tests about the Mean] [ws5] [2012-10-26 12:11:00] [7722d8427d2b2c713c1f0d5525f2f86c]
- RMPD        [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ws5] [2012-10-26 12:44:29] [7722d8427d2b2c713c1f0d5525f2f86c]
- RM D          [Two-Way ANOVA] [ws5] [2012-10-26 14:29:56] [7722d8427d2b2c713c1f0d5525f2f86c]
-   P               [Two-Way ANOVA] [Question 8] [2012-10-29 16:07:27] [ce0090a42f002b2795917a1b5d34ffb3] [Current]
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
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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
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0	0	'E'	0	0
0	1	'F'	1	0
0	1	'E'	1	0
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1	1	'F'	0	1
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0	0	'H'	0	1
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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
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0	0	'H'	0	0
0	0	'E'	0	1
0	1	'F'	1	1
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0	0	'H'	0	1
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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
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0	1	'E'	1	0
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0	0	'E'	0	0
0	0	'E'	0	0
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1	1	'H'	0	1
0	0	'H'	0	1
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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
0	0	'H'	0	1
0	1	'E'	1	1
0	0	'F'	0	0
0	0	'H'	0	1
0	0	'E'	0	1
0	0	'F'	0	0
0	0	'H'	0	0
0	0	'H'	0	1
0	1	'F'	1	1
0	1	'F'	1	1
0	0	'H'	0	1
0	0	'E'	0	0
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0	0	'E'	0	1
0	0	'E'	0	0
0	0	'F'	0	1
0	0	'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'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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184641&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184641&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184641&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'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
Response ~ Treatment_A * Treatment_B
means-0.0451.0450.0450.045-0.136-0.545

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & -0.045 & 1.045 & 0.045 & 0.045 & -0.136 & -0.545 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184641&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]-0.045[/C][C]1.045[/C][C]0.045[/C][C]0.045[/C][C]-0.136[/C][C]-0.545[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184641&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184641&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
means-0.0451.0450.0450.045-0.136-0.545






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A122.77422.774772.4010
Treatment_B10.0090.0050.1550.856
Treatment_A:Treatment_B10.4750.2378.0470.001
Residuals1113.2730.029 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 22.774 & 22.774 & 772.401 & 0 \tabularnewline
Treatment_B & 1 & 0.009 & 0.005 & 0.155 & 0.856 \tabularnewline
Treatment_A:Treatment_B & 1 & 0.475 & 0.237 & 8.047 & 0.001 \tabularnewline
Residuals & 111 & 3.273 & 0.029 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184641&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]22.774[/C][C]22.774[/C][C]772.401[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]0.009[/C][C]0.005[/C][C]0.155[/C][C]0.856[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]0.475[/C][C]0.237[/C][C]8.047[/C][C]0.001[/C][/ROW]
[ROW][C]Residuals[/C][C]111[/C][C]3.273[/C][C]0.029[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184641&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184641&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)
1
Treatment_A122.77422.774772.4010
Treatment_B10.0090.0050.1550.856
Treatment_A:Treatment_B10.4750.2378.0470.001
Residuals1113.2730.029






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.9360.8691.0030
F-E-0.014-0.1070.0790.935
H-E-0.021-0.1140.0720.857
H-F-0.007-0.0980.0840.982
1:E-0:E1.0450.8791.2120
0:F-0:E0.045-0.1130.2040.961
1:F-0:E0.9550.8041.1050
0:H-0:E0.045-0.0880.1790.921
1:H-0:E0.5450.1780.9130.001
0:F-1:E-1-1.174-0.8260
1:F-1:E-0.091-0.2580.0760.613
0:H-1:E-1-1.152-0.8480
1:H-1:E-0.5-0.875-0.1250.002
1:F-0:F0.9090.7511.0670
0:H-0:F0-0.1420.1421
1:H-0:F0.50.1290.8710.002
0:H-1:F-0.909-1.042-0.7760
1:H-1:F-0.409-0.777-0.0410.02
1:H-0:H0.50.1390.8610.001

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 0.936 & 0.869 & 1.003 & 0 \tabularnewline
F-E & -0.014 & -0.107 & 0.079 & 0.935 \tabularnewline
H-E & -0.021 & -0.114 & 0.072 & 0.857 \tabularnewline
H-F & -0.007 & -0.098 & 0.084 & 0.982 \tabularnewline
1:E-0:E & 1.045 & 0.879 & 1.212 & 0 \tabularnewline
0:F-0:E & 0.045 & -0.113 & 0.204 & 0.961 \tabularnewline
1:F-0:E & 0.955 & 0.804 & 1.105 & 0 \tabularnewline
0:H-0:E & 0.045 & -0.088 & 0.179 & 0.921 \tabularnewline
1:H-0:E & 0.545 & 0.178 & 0.913 & 0.001 \tabularnewline
0:F-1:E & -1 & -1.174 & -0.826 & 0 \tabularnewline
1:F-1:E & -0.091 & -0.258 & 0.076 & 0.613 \tabularnewline
0:H-1:E & -1 & -1.152 & -0.848 & 0 \tabularnewline
1:H-1:E & -0.5 & -0.875 & -0.125 & 0.002 \tabularnewline
1:F-0:F & 0.909 & 0.751 & 1.067 & 0 \tabularnewline
0:H-0:F & 0 & -0.142 & 0.142 & 1 \tabularnewline
1:H-0:F & 0.5 & 0.129 & 0.871 & 0.002 \tabularnewline
0:H-1:F & -0.909 & -1.042 & -0.776 & 0 \tabularnewline
1:H-1:F & -0.409 & -0.777 & -0.041 & 0.02 \tabularnewline
1:H-0:H & 0.5 & 0.139 & 0.861 & 0.001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184641&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]1-0[/C][C]0.936[/C][C]0.869[/C][C]1.003[/C][C]0[/C][/ROW]
[ROW][C]F-E[/C][C]-0.014[/C][C]-0.107[/C][C]0.079[/C][C]0.935[/C][/ROW]
[ROW][C]H-E[/C][C]-0.021[/C][C]-0.114[/C][C]0.072[/C][C]0.857[/C][/ROW]
[ROW][C]H-F[/C][C]-0.007[/C][C]-0.098[/C][C]0.084[/C][C]0.982[/C][/ROW]
[ROW][C]1:E-0:E[/C][C]1.045[/C][C]0.879[/C][C]1.212[/C][C]0[/C][/ROW]
[ROW][C]0:F-0:E[/C][C]0.045[/C][C]-0.113[/C][C]0.204[/C][C]0.961[/C][/ROW]
[ROW][C]1:F-0:E[/C][C]0.955[/C][C]0.804[/C][C]1.105[/C][C]0[/C][/ROW]
[ROW][C]0:H-0:E[/C][C]0.045[/C][C]-0.088[/C][C]0.179[/C][C]0.921[/C][/ROW]
[ROW][C]1:H-0:E[/C][C]0.545[/C][C]0.178[/C][C]0.913[/C][C]0.001[/C][/ROW]
[ROW][C]0:F-1:E[/C][C]-1[/C][C]-1.174[/C][C]-0.826[/C][C]0[/C][/ROW]
[ROW][C]1:F-1:E[/C][C]-0.091[/C][C]-0.258[/C][C]0.076[/C][C]0.613[/C][/ROW]
[ROW][C]0:H-1:E[/C][C]-1[/C][C]-1.152[/C][C]-0.848[/C][C]0[/C][/ROW]
[ROW][C]1:H-1:E[/C][C]-0.5[/C][C]-0.875[/C][C]-0.125[/C][C]0.002[/C][/ROW]
[ROW][C]1:F-0:F[/C][C]0.909[/C][C]0.751[/C][C]1.067[/C][C]0[/C][/ROW]
[ROW][C]0:H-0:F[/C][C]0[/C][C]-0.142[/C][C]0.142[/C][C]1[/C][/ROW]
[ROW][C]1:H-0:F[/C][C]0.5[/C][C]0.129[/C][C]0.871[/C][C]0.002[/C][/ROW]
[ROW][C]0:H-1:F[/C][C]-0.909[/C][C]-1.042[/C][C]-0.776[/C][C]0[/C][/ROW]
[ROW][C]1:H-1:F[/C][C]-0.409[/C][C]-0.777[/C][C]-0.041[/C][C]0.02[/C][/ROW]
[ROW][C]1:H-0:H[/C][C]0.5[/C][C]0.139[/C][C]0.861[/C][C]0.001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184641&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184641&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
1-00.9360.8691.0030
F-E-0.014-0.1070.0790.935
H-E-0.021-0.1140.0720.857
H-F-0.007-0.0980.0840.982
1:E-0:E1.0450.8791.2120
0:F-0:E0.045-0.1130.2040.961
1:F-0:E0.9550.8041.1050
0:H-0:E0.045-0.0880.1790.921
1:H-0:E0.5450.1780.9130.001
0:F-1:E-1-1.174-0.8260
1:F-1:E-0.091-0.2580.0760.613
0:H-1:E-1-1.152-0.8480
1:H-1:E-0.5-0.875-0.1250.002
1:F-0:F0.9090.7511.0670
0:H-0:F0-0.1420.1421
1:H-0:F0.50.1290.8710.002
0:H-1:F-0.909-1.042-0.7760
1:H-1:F-0.409-0.777-0.0410.02
1:H-0:H0.50.1390.8610.001






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group54.7280.001
111 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 4.728 & 0.001 \tabularnewline
  & 111 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=184641&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]4.728[/C][C]0.001[/C][/ROW]
[ROW][C] [/C][C]111[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=184641&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=184641&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)
Group54.7280.001
111


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
Parameters (R input):
par1 = 4 ; 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')