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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationTue, 12 Nov 2013 08:23:59 -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/2013/Nov/12/t13842626900kb3ioqeb9hgwfc.htm/, Retrieved Thu, 02 May 2024 14:33:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=224370, Retrieved Thu, 02 May 2024 14:33:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA wit...] [2009-11-29 13:09:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA for...] [2009-12-01 13:05:10] [3fdd735c61ad38cbc9b3393dc997cdb7]
- R P     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [CARE date with Tu...] [2009-12-01 18:33:48] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE Data with Tu...] [2010-11-23 12:09:38] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IQ and Mothers Age] [2011-11-21 16:34:08] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R PD          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [fdskjnvlds] [2013-11-11 20:57:34] [74be16979710d4c4e7c6647856088456]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [HK] [2013-11-12 13:23:59] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6	36
8	56
8	48
7	32
5	44
7	39
8	34
9	41
9	50
3	39
9	62
7	52
9	37
8	50
6	41
7	55
8	41
9	56
7	39
6	52
8	46
7	44
8	41
9	50
9	50
7	44
4	52
7	54
7	44
9	52
7	37
9	52
10	50
5	36
6	50
9	52
9	55
8	31
6	36
6	49
5	42
8	37
8	41
5	30
6	52
9	30
4	44
8	66
9	48
7	43
7	57
6	46
9	54
9	48
8	48
6	62
10	58
8	58
7	62
8	46
3	34
8	66
10	52
7	55
5	55
10	57
5	56
8	55
9	56
6	54
9	55
8	46
5	52
8	32
3	44
7	46
8	59
10	46
9	46
10	54
9	66
8	56
8	59
8	57
9	52
4	48
6	44
7	41
4	50
9	48
7	48
8	59
8	46
7	54
7	55
9	54
8	59
8	44
9	54
9	52
10	66
7	44
8	57
5	39
9	60
8	45
7	41
8	50
8	39
7	43
6	48
7	37
7	58
6	46
6	43
7	44
9	34
6	30
10	50
4	39
8	37
7	55
5	39
9	36
8	43
9	50
8	55
8	43
9	60
8	48
9	30
7	43
6	39
8	52
6	39
5	39
3	56
6	59
8	46
7	57
8	50
6	54
9	50
9	60
10	59
7	41
5	48
8	59
9	60
8	56
4	51

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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224370&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224370&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224370&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 Ronald Aylmer Fisher' @ fisher.wessa.net






ANOVA Model
MC30VRB ~ MWARM30
means54.667-11.417-7.333-11.03-8.351-7.632-5.642-4.364

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MWARM30 \tabularnewline
means & 54.667 & -11.417 & -7.333 & -11.03 & -8.351 & -7.632 & -5.642 & -4.364 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224370&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]54.667[/C][C]-11.417[/C][C]-7.333[/C][C]-11.03[/C][C]-8.351[/C][C]-7.632[/C][C]-5.642[/C][C]-4.364[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224370&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224370&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
MC30VRB ~ MWARM30
means54.667-11.417-7.333-11.03-8.351-7.632-5.642-4.364






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM307986.342140.9062.0350.055
Residuals1439901.64469.242 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 7 & 986.342 & 140.906 & 2.035 & 0.055 \tabularnewline
Residuals & 143 & 9901.644 & 69.242 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224370&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]MWARM30[/C][C]7[/C][C]986.342[/C][C]140.906[/C][C]2.035[/C][C]0.055[/C][/ROW]
[ROW][C]Residuals[/C][C]143[/C][C]9901.644[/C][C]69.242[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224370&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224370&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)
MWARM307986.342140.9062.0350.055
Residuals1439901.64469.242






Tukey Honest Significant Difference Comparisons
difflwruprp adj
3-10-11.417-26.83.9660.31
4-10-7.333-20.8256.1580.705
5-10-11.03-22.5360.4750.071
6-10-8.351-18.7092.0080.213
7-10-7.632-17.42.1350.248
8-10-5.642-15.0863.8030.596
9-10-4.364-13.995.2630.858
4-34.083-12.44120.6070.995
5-30.386-14.5615.3331
6-33.066-11.01717.1480.998
7-33.784-9.86917.4380.99
8-35.775-7.64919.1990.889
9-37.053-6.520.6060.749
5-4-3.697-16.6899.2950.988
6-4-1.018-13.00510.971
7-4-0.299-11.7811.1821
8-41.692-9.51512.8991
9-42.97-8.39114.3310.993
6-52.679-7.01912.3780.99
7-53.398-5.66712.4630.943
8-55.389-3.32714.1040.552
9-56.667-2.24615.5790.3
7-60.719-6.8378.2741
8-62.709-4.4239.8420.94
9-63.987-3.38511.3590.71
8-71.991-4.2538.2340.976
9-73.269-3.2479.7840.783
9-81.278-4.7427.2980.998

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
3-10 & -11.417 & -26.8 & 3.966 & 0.31 \tabularnewline
4-10 & -7.333 & -20.825 & 6.158 & 0.705 \tabularnewline
5-10 & -11.03 & -22.536 & 0.475 & 0.071 \tabularnewline
6-10 & -8.351 & -18.709 & 2.008 & 0.213 \tabularnewline
7-10 & -7.632 & -17.4 & 2.135 & 0.248 \tabularnewline
8-10 & -5.642 & -15.086 & 3.803 & 0.596 \tabularnewline
9-10 & -4.364 & -13.99 & 5.263 & 0.858 \tabularnewline
4-3 & 4.083 & -12.441 & 20.607 & 0.995 \tabularnewline
5-3 & 0.386 & -14.56 & 15.333 & 1 \tabularnewline
6-3 & 3.066 & -11.017 & 17.148 & 0.998 \tabularnewline
7-3 & 3.784 & -9.869 & 17.438 & 0.99 \tabularnewline
8-3 & 5.775 & -7.649 & 19.199 & 0.889 \tabularnewline
9-3 & 7.053 & -6.5 & 20.606 & 0.749 \tabularnewline
5-4 & -3.697 & -16.689 & 9.295 & 0.988 \tabularnewline
6-4 & -1.018 & -13.005 & 10.97 & 1 \tabularnewline
7-4 & -0.299 & -11.78 & 11.182 & 1 \tabularnewline
8-4 & 1.692 & -9.515 & 12.899 & 1 \tabularnewline
9-4 & 2.97 & -8.391 & 14.331 & 0.993 \tabularnewline
6-5 & 2.679 & -7.019 & 12.378 & 0.99 \tabularnewline
7-5 & 3.398 & -5.667 & 12.463 & 0.943 \tabularnewline
8-5 & 5.389 & -3.327 & 14.104 & 0.552 \tabularnewline
9-5 & 6.667 & -2.246 & 15.579 & 0.3 \tabularnewline
7-6 & 0.719 & -6.837 & 8.274 & 1 \tabularnewline
8-6 & 2.709 & -4.423 & 9.842 & 0.94 \tabularnewline
9-6 & 3.987 & -3.385 & 11.359 & 0.71 \tabularnewline
8-7 & 1.991 & -4.253 & 8.234 & 0.976 \tabularnewline
9-7 & 3.269 & -3.247 & 9.784 & 0.783 \tabularnewline
9-8 & 1.278 & -4.742 & 7.298 & 0.998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224370&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]3-10[/C][C]-11.417[/C][C]-26.8[/C][C]3.966[/C][C]0.31[/C][/ROW]
[ROW][C]4-10[/C][C]-7.333[/C][C]-20.825[/C][C]6.158[/C][C]0.705[/C][/ROW]
[ROW][C]5-10[/C][C]-11.03[/C][C]-22.536[/C][C]0.475[/C][C]0.071[/C][/ROW]
[ROW][C]6-10[/C][C]-8.351[/C][C]-18.709[/C][C]2.008[/C][C]0.213[/C][/ROW]
[ROW][C]7-10[/C][C]-7.632[/C][C]-17.4[/C][C]2.135[/C][C]0.248[/C][/ROW]
[ROW][C]8-10[/C][C]-5.642[/C][C]-15.086[/C][C]3.803[/C][C]0.596[/C][/ROW]
[ROW][C]9-10[/C][C]-4.364[/C][C]-13.99[/C][C]5.263[/C][C]0.858[/C][/ROW]
[ROW][C]4-3[/C][C]4.083[/C][C]-12.441[/C][C]20.607[/C][C]0.995[/C][/ROW]
[ROW][C]5-3[/C][C]0.386[/C][C]-14.56[/C][C]15.333[/C][C]1[/C][/ROW]
[ROW][C]6-3[/C][C]3.066[/C][C]-11.017[/C][C]17.148[/C][C]0.998[/C][/ROW]
[ROW][C]7-3[/C][C]3.784[/C][C]-9.869[/C][C]17.438[/C][C]0.99[/C][/ROW]
[ROW][C]8-3[/C][C]5.775[/C][C]-7.649[/C][C]19.199[/C][C]0.889[/C][/ROW]
[ROW][C]9-3[/C][C]7.053[/C][C]-6.5[/C][C]20.606[/C][C]0.749[/C][/ROW]
[ROW][C]5-4[/C][C]-3.697[/C][C]-16.689[/C][C]9.295[/C][C]0.988[/C][/ROW]
[ROW][C]6-4[/C][C]-1.018[/C][C]-13.005[/C][C]10.97[/C][C]1[/C][/ROW]
[ROW][C]7-4[/C][C]-0.299[/C][C]-11.78[/C][C]11.182[/C][C]1[/C][/ROW]
[ROW][C]8-4[/C][C]1.692[/C][C]-9.515[/C][C]12.899[/C][C]1[/C][/ROW]
[ROW][C]9-4[/C][C]2.97[/C][C]-8.391[/C][C]14.331[/C][C]0.993[/C][/ROW]
[ROW][C]6-5[/C][C]2.679[/C][C]-7.019[/C][C]12.378[/C][C]0.99[/C][/ROW]
[ROW][C]7-5[/C][C]3.398[/C][C]-5.667[/C][C]12.463[/C][C]0.943[/C][/ROW]
[ROW][C]8-5[/C][C]5.389[/C][C]-3.327[/C][C]14.104[/C][C]0.552[/C][/ROW]
[ROW][C]9-5[/C][C]6.667[/C][C]-2.246[/C][C]15.579[/C][C]0.3[/C][/ROW]
[ROW][C]7-6[/C][C]0.719[/C][C]-6.837[/C][C]8.274[/C][C]1[/C][/ROW]
[ROW][C]8-6[/C][C]2.709[/C][C]-4.423[/C][C]9.842[/C][C]0.94[/C][/ROW]
[ROW][C]9-6[/C][C]3.987[/C][C]-3.385[/C][C]11.359[/C][C]0.71[/C][/ROW]
[ROW][C]8-7[/C][C]1.991[/C][C]-4.253[/C][C]8.234[/C][C]0.976[/C][/ROW]
[ROW][C]9-7[/C][C]3.269[/C][C]-3.247[/C][C]9.784[/C][C]0.783[/C][/ROW]
[ROW][C]9-8[/C][C]1.278[/C][C]-4.742[/C][C]7.298[/C][C]0.998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224370&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224370&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
3-10-11.417-26.83.9660.31
4-10-7.333-20.8256.1580.705
5-10-11.03-22.5360.4750.071
6-10-8.351-18.7092.0080.213
7-10-7.632-17.42.1350.248
8-10-5.642-15.0863.8030.596
9-10-4.364-13.995.2630.858
4-34.083-12.44120.6070.995
5-30.386-14.5615.3331
6-33.066-11.01717.1480.998
7-33.784-9.86917.4380.99
8-35.775-7.64919.1990.889
9-37.053-6.520.6060.749
5-4-3.697-16.6899.2950.988
6-4-1.018-13.00510.971
7-4-0.299-11.7811.1821
8-41.692-9.51512.8991
9-42.97-8.39114.3310.993
6-52.679-7.01912.3780.99
7-53.398-5.66712.4630.943
8-55.389-3.32714.1040.552
9-56.667-2.24615.5790.3
7-60.719-6.8378.2741
8-62.709-4.4239.8420.94
9-63.987-3.38511.3590.71
8-71.991-4.2538.2340.976
9-73.269-3.2479.7840.783
9-81.278-4.7427.2980.998






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group70.5540.792
143 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 7 & 0.554 & 0.792 \tabularnewline
  & 143 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224370&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]7[/C][C]0.554[/C][C]0.792[/C][/ROW]
[ROW][C] [/C][C]143[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224370&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224370&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)
Group70.5540.792
143


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, 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$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$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)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], 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, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
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(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
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')