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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationThu, 22 Dec 2016 19:34:12 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/22/t1482431694kyo6lg50te6xaek.htm/, Retrieved Mon, 29 Apr 2024 07:17:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302618, Retrieved Mon, 29 Apr 2024 07:17:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [one way anova ITH...] [2016-12-22 18:34:12] [6f830dc7e8de22be3233942ffbe3aaba] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14	10
19	13
17	14
17	12
15	12
20	13
15	13
19	13
15	13
15	14
19	14
16	12
20	12
18	11
15	12
14	14
20	12
16	11
16	13
16	13
10	12
19	13
19	12
16	13
15	11
18	12
17	12
19	13
17	13
14	10
19	12
20	13
5	13
19	10
16	14
15	12
16	10
18	10
16	14
15	12
17	14
14	10
20	13
19	12
7	12
13	13
16	12
16	10
18	14
18	15
16	14
17	8
19	11
16	10
19	12
13	14
16	12
13	12
12	14
17	13
17	13
17	13
16	12
16	10
14	14
16	11
13	10
16	13
14	12
20	12
12	11
13	10
18	14
14	12
19	13
18	11
14	10
18	14
19	13
15	7
14	13
17	13
19	13
13	15
19	13
18	14
20	12
15	13
15	11
15	12
20	14
15	13
19	14
18	12
18	12
15	13
20	14
17	13
18	13
19	12
20	10
13	12
17	13
15	12
16	13
18	12
18	12
14	12
15	11
12	12
17	9
14	14
18	12
17	13
17	13
20	13
16	11
14	12
15	11
18	12
20	12
17	13
17	12
17	13
17	13
15	12
17	12
18	8
17	12
20	13
15	10
16	8
15	12
18	13
15	12
18	15
20	14
19	10
14	11
16	12
15	10
17	14
18	10
20	15
17	11
18	12
15	9
16	12
11	13
15	12
18	9
17	12
16	14
12	11
19	12
18	14
15	12
17	15
19	11
18	12
19	12
16	10
16	12
16	11
14	11

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302618&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]4 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302618&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302618&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center






ANOVA Model
ITHSUM ~ TDVCSUM-4
means15.889-0.1830.50.940.851.311-0.8891.1110.778

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
ITHSUM  ~  TDVCSUM-4 \tabularnewline
means & 15.889 & -0.183 & 0.5 & 0.94 & 0.85 & 1.311 & -0.889 & 1.111 & 0.778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302618&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]ITHSUM  ~  TDVCSUM-4[/C][/ROW]
[ROW][C]means[/C][C]15.889[/C][C]-0.183[/C][C]0.5[/C][C]0.94[/C][C]0.85[/C][C]1.311[/C][C]-0.889[/C][C]1.111[/C][C]0.778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302618&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302618&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
ITHSUM ~ TDVCSUM-4
means15.889-0.1830.50.940.851.311-0.8891.1110.778






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
TDVCSUM-4829.0623.6330.5920.784
Residuals156957.8476.14 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
TDVCSUM-4 & 8 & 29.062 & 3.633 & 0.592 & 0.784 \tabularnewline
Residuals & 156 & 957.847 & 6.14 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302618&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]TDVCSUM-4[/C][C]8[/C][C]29.062[/C][C]3.633[/C][C]0.592[/C][C]0.784[/C][/ROW]
[ROW][C]Residuals[/C][C]156[/C][C]957.847[/C][C]6.14[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302618&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302618&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)
TDVCSUM-4829.0623.6330.5920.784
Residuals156957.8476.14






Tukey Honest Significant Difference Comparisons
difflwruprp adj
11-10-0.183-2.8192.4531
12-100.5-1.6222.6220.998
13-100.94-1.2643.1440.917
14-100.85-1.6033.3030.975
15-101.311-2.635.2520.981
7-10-0.889-8.8987.121
8-101.111-3.755.9720.998
9-100.778-4.0835.6391
12-110.683-1.4852.8510.986
13-111.123-1.1253.3720.819
14-111.033-1.463.5260.929
15-111.494-2.4725.460.959
7-11-0.706-8.7277.3151
8-111.294-3.5876.1760.996
9-110.961-3.9215.8420.999
13-120.44-1.1742.0550.995
14-120.35-1.5912.2911
15-120.811-2.8334.4550.999
7-12-1.389-9.2566.4781
8-120.611-4.0135.2351
9-120.278-4.3464.9021
14-13-0.09-2.1211.9411
15-130.371-3.3224.0631
7-13-1.829-9.7196.060.998
8-130.171-4.4924.8331
9-13-0.163-4.8254.51
15-140.461-3.3864.3071
7-14-1.739-9.7026.2240.999
8-140.261-4.5245.0461
9-14-0.072-4.8584.7131
7-15-2.2-10.7396.3390.996
8-15-0.2-5.8935.4931
9-15-0.533-6.2265.1591
8-72-7.00111.0010.999
9-71.667-7.33410.6681
9-8-0.333-6.6986.0311

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
11-10 & -0.183 & -2.819 & 2.453 & 1 \tabularnewline
12-10 & 0.5 & -1.622 & 2.622 & 0.998 \tabularnewline
13-10 & 0.94 & -1.264 & 3.144 & 0.917 \tabularnewline
14-10 & 0.85 & -1.603 & 3.303 & 0.975 \tabularnewline
15-10 & 1.311 & -2.63 & 5.252 & 0.981 \tabularnewline
7-10 & -0.889 & -8.898 & 7.12 & 1 \tabularnewline
8-10 & 1.111 & -3.75 & 5.972 & 0.998 \tabularnewline
9-10 & 0.778 & -4.083 & 5.639 & 1 \tabularnewline
12-11 & 0.683 & -1.485 & 2.851 & 0.986 \tabularnewline
13-11 & 1.123 & -1.125 & 3.372 & 0.819 \tabularnewline
14-11 & 1.033 & -1.46 & 3.526 & 0.929 \tabularnewline
15-11 & 1.494 & -2.472 & 5.46 & 0.959 \tabularnewline
7-11 & -0.706 & -8.727 & 7.315 & 1 \tabularnewline
8-11 & 1.294 & -3.587 & 6.176 & 0.996 \tabularnewline
9-11 & 0.961 & -3.921 & 5.842 & 0.999 \tabularnewline
13-12 & 0.44 & -1.174 & 2.055 & 0.995 \tabularnewline
14-12 & 0.35 & -1.591 & 2.291 & 1 \tabularnewline
15-12 & 0.811 & -2.833 & 4.455 & 0.999 \tabularnewline
7-12 & -1.389 & -9.256 & 6.478 & 1 \tabularnewline
8-12 & 0.611 & -4.013 & 5.235 & 1 \tabularnewline
9-12 & 0.278 & -4.346 & 4.902 & 1 \tabularnewline
14-13 & -0.09 & -2.121 & 1.941 & 1 \tabularnewline
15-13 & 0.371 & -3.322 & 4.063 & 1 \tabularnewline
7-13 & -1.829 & -9.719 & 6.06 & 0.998 \tabularnewline
8-13 & 0.171 & -4.492 & 4.833 & 1 \tabularnewline
9-13 & -0.163 & -4.825 & 4.5 & 1 \tabularnewline
15-14 & 0.461 & -3.386 & 4.307 & 1 \tabularnewline
7-14 & -1.739 & -9.702 & 6.224 & 0.999 \tabularnewline
8-14 & 0.261 & -4.524 & 5.046 & 1 \tabularnewline
9-14 & -0.072 & -4.858 & 4.713 & 1 \tabularnewline
7-15 & -2.2 & -10.739 & 6.339 & 0.996 \tabularnewline
8-15 & -0.2 & -5.893 & 5.493 & 1 \tabularnewline
9-15 & -0.533 & -6.226 & 5.159 & 1 \tabularnewline
8-7 & 2 & -7.001 & 11.001 & 0.999 \tabularnewline
9-7 & 1.667 & -7.334 & 10.668 & 1 \tabularnewline
9-8 & -0.333 & -6.698 & 6.031 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302618&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]11-10[/C][C]-0.183[/C][C]-2.819[/C][C]2.453[/C][C]1[/C][/ROW]
[ROW][C]12-10[/C][C]0.5[/C][C]-1.622[/C][C]2.622[/C][C]0.998[/C][/ROW]
[ROW][C]13-10[/C][C]0.94[/C][C]-1.264[/C][C]3.144[/C][C]0.917[/C][/ROW]
[ROW][C]14-10[/C][C]0.85[/C][C]-1.603[/C][C]3.303[/C][C]0.975[/C][/ROW]
[ROW][C]15-10[/C][C]1.311[/C][C]-2.63[/C][C]5.252[/C][C]0.981[/C][/ROW]
[ROW][C]7-10[/C][C]-0.889[/C][C]-8.898[/C][C]7.12[/C][C]1[/C][/ROW]
[ROW][C]8-10[/C][C]1.111[/C][C]-3.75[/C][C]5.972[/C][C]0.998[/C][/ROW]
[ROW][C]9-10[/C][C]0.778[/C][C]-4.083[/C][C]5.639[/C][C]1[/C][/ROW]
[ROW][C]12-11[/C][C]0.683[/C][C]-1.485[/C][C]2.851[/C][C]0.986[/C][/ROW]
[ROW][C]13-11[/C][C]1.123[/C][C]-1.125[/C][C]3.372[/C][C]0.819[/C][/ROW]
[ROW][C]14-11[/C][C]1.033[/C][C]-1.46[/C][C]3.526[/C][C]0.929[/C][/ROW]
[ROW][C]15-11[/C][C]1.494[/C][C]-2.472[/C][C]5.46[/C][C]0.959[/C][/ROW]
[ROW][C]7-11[/C][C]-0.706[/C][C]-8.727[/C][C]7.315[/C][C]1[/C][/ROW]
[ROW][C]8-11[/C][C]1.294[/C][C]-3.587[/C][C]6.176[/C][C]0.996[/C][/ROW]
[ROW][C]9-11[/C][C]0.961[/C][C]-3.921[/C][C]5.842[/C][C]0.999[/C][/ROW]
[ROW][C]13-12[/C][C]0.44[/C][C]-1.174[/C][C]2.055[/C][C]0.995[/C][/ROW]
[ROW][C]14-12[/C][C]0.35[/C][C]-1.591[/C][C]2.291[/C][C]1[/C][/ROW]
[ROW][C]15-12[/C][C]0.811[/C][C]-2.833[/C][C]4.455[/C][C]0.999[/C][/ROW]
[ROW][C]7-12[/C][C]-1.389[/C][C]-9.256[/C][C]6.478[/C][C]1[/C][/ROW]
[ROW][C]8-12[/C][C]0.611[/C][C]-4.013[/C][C]5.235[/C][C]1[/C][/ROW]
[ROW][C]9-12[/C][C]0.278[/C][C]-4.346[/C][C]4.902[/C][C]1[/C][/ROW]
[ROW][C]14-13[/C][C]-0.09[/C][C]-2.121[/C][C]1.941[/C][C]1[/C][/ROW]
[ROW][C]15-13[/C][C]0.371[/C][C]-3.322[/C][C]4.063[/C][C]1[/C][/ROW]
[ROW][C]7-13[/C][C]-1.829[/C][C]-9.719[/C][C]6.06[/C][C]0.998[/C][/ROW]
[ROW][C]8-13[/C][C]0.171[/C][C]-4.492[/C][C]4.833[/C][C]1[/C][/ROW]
[ROW][C]9-13[/C][C]-0.163[/C][C]-4.825[/C][C]4.5[/C][C]1[/C][/ROW]
[ROW][C]15-14[/C][C]0.461[/C][C]-3.386[/C][C]4.307[/C][C]1[/C][/ROW]
[ROW][C]7-14[/C][C]-1.739[/C][C]-9.702[/C][C]6.224[/C][C]0.999[/C][/ROW]
[ROW][C]8-14[/C][C]0.261[/C][C]-4.524[/C][C]5.046[/C][C]1[/C][/ROW]
[ROW][C]9-14[/C][C]-0.072[/C][C]-4.858[/C][C]4.713[/C][C]1[/C][/ROW]
[ROW][C]7-15[/C][C]-2.2[/C][C]-10.739[/C][C]6.339[/C][C]0.996[/C][/ROW]
[ROW][C]8-15[/C][C]-0.2[/C][C]-5.893[/C][C]5.493[/C][C]1[/C][/ROW]
[ROW][C]9-15[/C][C]-0.533[/C][C]-6.226[/C][C]5.159[/C][C]1[/C][/ROW]
[ROW][C]8-7[/C][C]2[/C][C]-7.001[/C][C]11.001[/C][C]0.999[/C][/ROW]
[ROW][C]9-7[/C][C]1.667[/C][C]-7.334[/C][C]10.668[/C][C]1[/C][/ROW]
[ROW][C]9-8[/C][C]-0.333[/C][C]-6.698[/C][C]6.031[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302618&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302618&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
11-10-0.183-2.8192.4531
12-100.5-1.6222.6220.998
13-100.94-1.2643.1440.917
14-100.85-1.6033.3030.975
15-101.311-2.635.2520.981
7-10-0.889-8.8987.121
8-101.111-3.755.9720.998
9-100.778-4.0835.6391
12-110.683-1.4852.8510.986
13-111.123-1.1253.3720.819
14-111.033-1.463.5260.929
15-111.494-2.4725.460.959
7-11-0.706-8.7277.3151
8-111.294-3.5876.1760.996
9-110.961-3.9215.8420.999
13-120.44-1.1742.0550.995
14-120.35-1.5912.2911
15-120.811-2.8334.4550.999
7-12-1.389-9.2566.4781
8-120.611-4.0135.2351
9-120.278-4.3464.9021
14-13-0.09-2.1211.9411
15-130.371-3.3224.0631
7-13-1.829-9.7196.060.998
8-130.171-4.4924.8331
9-13-0.163-4.8254.51
15-140.461-3.3864.3071
7-14-1.739-9.7026.2240.999
8-140.261-4.5245.0461
9-14-0.072-4.8584.7131
7-15-2.2-10.7396.3390.996
8-15-0.2-5.8935.4931
9-15-0.533-6.2265.1591
8-72-7.00111.0010.999
9-71.667-7.33410.6681
9-8-0.333-6.6986.0311






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group80.5830.791
156 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 0.583 & 0.791 \tabularnewline
  & 156 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302618&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]8[/C][C]0.583[/C][C]0.791[/C][/ROW]
[ROW][C] [/C][C]156[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302618&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302618&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)
Group80.5830.791
156


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Exact Pearson Chi-Squared by Simulation ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; 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){
'Tukey Plot'
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<-leveneTest(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')