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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, 11 Dec 2014 18:26:47 +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/2014/Dec/11/t1418322457tn3s2h84ifw7e7w.htm/, Retrieved Thu, 16 May 2024 13:56:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266254, Retrieved Thu, 16 May 2024 13:56:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact72

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)] [] [2014-12-11 18:26:47] [ec71b09431fe59ba6fc828a3f51756a9] [Current]
- RMPD    [Skewness and Kurtosis Test] [] [2014-12-17 11:57:18] [02fb6cbf799bcf1e525e4e01c2f27ada]
- RMPD    [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-12-17 12:30:51] [02fb6cbf799bcf1e525e4e01c2f27ada]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.56 12.9
0.79 7.4
0.68 12.2
0.66 12.8
0.37 7.4
0.71 6.7
0.35 12.6
0.55 14.8
0.76 13.3
0.49 11.1
0.56 8.2
0.60 11.4
0.44 6.4
0.55 10.6
0.58 12.0
0.40 6.3
0.42 11.3
0.58 11.9
0.64 9.3
0.58 9.6
0.44 10.0
0.46 6.4
0.64 13.8
0.59 10.8
0.54 13.8
0.71 11.7
0.20 10.9
0.89 16.1
0.55 13.4
0.71 9.9
0.48 11.5
0.49 8.3
0.58 11.7
0.78 6.1
0.71 9.0
0.51 9.7
0.65 10.8
0.68 10.3
0.24 10.4
0.36 12.7
0.65 9.3
0.79 11.8
0.67 5.9
0.74 11.4
0.72 13.0
0.73 10.8
0.58 12.3
0.67 11.3
0.43 11.8
0.59 7.9
0.43 12.7
0.80 12.3
0.74 11.6
0.43 6.7
0.72 10.9
0.50 12.1
0.45 13.3
0.88 10.1
0.67 5.7
0.32 14.3
0.20 8.0
0.84 13.3
0.83 9.3
0.65 12.5
0.74 7.6
0.53 15.9
0.58 9.2
0.65 9.1
0.64 11.1
0.60 13.0
0.52 14.5
0.53 12.2
0.73 12.3
0.52 11.4
0.61 8.8
0.73 14.6
0.79 7.3
0.29 12.6
0.86 NA
0.37 13.0
0.68 12.6
0.52 13.2
0.26 9.9
0.74 7.7
0.72 10.5
0.24 13.4
0.71 10.9
0.59 4.3
0.27 10.3
0.57 11.8
0.51 11.2
0.69 11.4
0.69 8.6
0.50 13.2
0.63 12.6
0.65 5.6
0.54 9.9
0.69 8.8
0.52 7.7
0.53 9.0
0.74 7.3
0.73 11.4
0.75 13.6
0.70 7.9
0.69 10.7
0.57 10.3
0.14 8.3
0.42 9.6
0.48 14.2
0.27 8.5
0.21 13.5
0.41 4.9
0.56 6.4
0.44 9.6
0.52 11.6
0.59 11.1
0.73 4.35
0.79 12.7
0.67 18.1
0.88 17.85
0.96 16.6
0.43 12.6
0.84 17.1
0.81 19.1
0.67 16.1
0.45 13.35
0.58 18.4
0.70 14.7
0.61 10.6
0.44 12.6
0.54 16.2
0.41 13.6
0.66 18.9
0.83 14.1
0.88 14.5
0.40 16.15
0.54 14.75
0.60 14.8
0.57 12.45
0.59 12.65
0.81 17.35
0.51 8.6
0.65 18.4
0.59 16.1
0.68 11.6
0.65 17.75
0.06 15.25
0.74 17.65
0.29 15.6
0.73 16.35
0.54 17.65
0.39 13.6
0.27 11.7
0.40 14.35
0.20 14.75
0.85 18.25
0.42 9.9
0.68 16
0.72 18.25
0.52 16.85
0.78 14.6
0.60 13.85
0.93 18.95
0.73 15.6
0.81 14.85
0.51 11.75
0.86 18.45
0.67 15.9
0.50 17.1
0.74 16.1
0.85 19.9
0.75 10.95
0.83 18.45
0.82 15.1
0.58 15
0.72 11.35
0.89 15.95
0.51 18.1
0.75 14.6
0.84 15.4
0.84 15.4
0.59 17.6
0.64 13.35
0.45 19.1
0.57 15.35
0.58 7.6
0.72 13.4
0.38 13.9
0.68 19.1
0.45 15.25
0.55 12.9
0.73 16.1
0.73 17.35
0.73 13.15
0.71 12.15
0.38 12.6
0.79 10.35
0.32 15.4
0.62 9.6
0.42 18.2
0.45 13.6
0.97 14.85
0.67 14.75
0.08 14.1
0.49 14.9
0.66 16.25
0.67 19.25
0.55 13.6
0.55 13.6
0.49 15.65
0.56 12.75
0.69 14.6
0.47 9.85
0.68 12.65
0.43 11.9
0.00 19.2
0.48 16.6
0.77 11.2
0.71 15.25
0.43 11.9
0.50 13.2
0.68 16.35
0.34 12.4
0.47 15.85
0.33 14.35
0.80 18.15
0.74 11.15
0.82 15.65
0.57 17.75
0.46 7.65
0.91 12.35
0.41 15.6
0.64 19.3
0.58 15.2
0.45 17.1
0.77 15.6
0.67 18.4
0.53 19.05
0.07 18.55
0.65 19.1
0.76 13.1
0.56 12.85
0.07 9.5
0.72 4.5
0.61 11.85
0.47 13.6
0.06 11.7
0.37 12.4
0.76 13.35
0.47 11.4
0.55 14.9
0.85 19.9
0.77 17.75
0.79 11.2
0.70 14.6
0.46 17.6
0.51 14.05
0.65 16.1
0.57 13.35
0.68 11.85
0.52 11.95
0.70 14.75
0.46 15.15
0.88 13.2
0.76 16.85
0.74 7.85
0.56 7.7
0.47 12.6
0.44 7.85
0.75 10.95
0.78 12.35
0.26 9.95
0.55 14.9
0.49 16.65
0.81 13.4
0.45 13.95
0.39 15.7
0.89 16.85
0.66 10.95
0.34 15.35
0.84 12.2
0.05 15.1
0.79 17.75
0.60 15.2
0.69 14.6
0.58 16.65
0.66 8.1

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'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266254&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266254&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266254&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'George Udny Yule' @ yule.wessa.net






ANOVA Model
Totaal ~ TOT
means0.440.880.5070.790.240.720.580.690.6570.5430.720.5730.740.690.5450.720.6250.480.6470.4050.510.5970.6450.480.520.580.50.710.6830.7030.8450.3550.570.650.4590.6350.5270.560.660.560.5550.5630.760.730.60.6830.6050.580.210.510.590.60.380.450.510.4550.480.320.3650.70.7230.70.5280.5750.890.530.580.4350.460.590.4070.4550.6670.550.6550.390.470.60.890.680.7120.40.540.660.7050.720.5350.7230.5970.770.5250.640.6950.880.590.80.420.7850.6330.8450.070.660.930.530.64800.670.640.850.590.730.720.410.650.670.670.780.40.4870.570.7650.580.660.460.6070.590.6450.20.660.560.3150.270.60.650.620.650.580.7070.070.5150.510.470.4830.260.86

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Totaal  ~  TOT \tabularnewline
means & 0.44 & 0.88 & 0.507 & 0.79 & 0.24 & 0.72 & 0.58 & 0.69 & 0.657 & 0.543 & 0.72 & 0.573 & 0.74 & 0.69 & 0.545 & 0.72 & 0.625 & 0.48 & 0.647 & 0.405 & 0.51 & 0.597 & 0.645 & 0.48 & 0.52 & 0.58 & 0.5 & 0.71 & 0.683 & 0.703 & 0.845 & 0.355 & 0.57 & 0.65 & 0.459 & 0.635 & 0.527 & 0.56 & 0.66 & 0.56 & 0.555 & 0.563 & 0.76 & 0.73 & 0.6 & 0.683 & 0.605 & 0.58 & 0.21 & 0.51 & 0.59 & 0.6 & 0.38 & 0.45 & 0.51 & 0.455 & 0.48 & 0.32 & 0.365 & 0.7 & 0.723 & 0.7 & 0.528 & 0.575 & 0.89 & 0.53 & 0.58 & 0.435 & 0.46 & 0.59 & 0.407 & 0.455 & 0.667 & 0.55 & 0.655 & 0.39 & 0.47 & 0.6 & 0.89 & 0.68 & 0.712 & 0.4 & 0.54 & 0.66 & 0.705 & 0.72 & 0.535 & 0.723 & 0.597 & 0.77 & 0.525 & 0.64 & 0.695 & 0.88 & 0.59 & 0.8 & 0.42 & 0.785 & 0.633 & 0.845 & 0.07 & 0.66 & 0.93 & 0.53 & 0.648 & 0 & 0.67 & 0.64 & 0.85 & 0.59 & 0.73 & 0.72 & 0.41 & 0.65 & 0.67 & 0.67 & 0.78 & 0.4 & 0.487 & 0.57 & 0.765 & 0.58 & 0.66 & 0.46 & 0.607 & 0.59 & 0.645 & 0.2 & 0.66 & 0.56 & 0.315 & 0.27 & 0.6 & 0.65 & 0.62 & 0.65 & 0.58 & 0.707 & 0.07 & 0.515 & 0.51 & 0.47 & 0.483 & 0.26 & 0.86 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266254&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]Totaal  ~  TOT[/C][/ROW]
[ROW][C]means[/C][C]0.44[/C][C]0.88[/C][C]0.507[/C][C]0.79[/C][C]0.24[/C][C]0.72[/C][C]0.58[/C][C]0.69[/C][C]0.657[/C][C]0.543[/C][C]0.72[/C][C]0.573[/C][C]0.74[/C][C]0.69[/C][C]0.545[/C][C]0.72[/C][C]0.625[/C][C]0.48[/C][C]0.647[/C][C]0.405[/C][C]0.51[/C][C]0.597[/C][C]0.645[/C][C]0.48[/C][C]0.52[/C][C]0.58[/C][C]0.5[/C][C]0.71[/C][C]0.683[/C][C]0.703[/C][C]0.845[/C][C]0.355[/C][C]0.57[/C][C]0.65[/C][C]0.459[/C][C]0.635[/C][C]0.527[/C][C]0.56[/C][C]0.66[/C][C]0.56[/C][C]0.555[/C][C]0.563[/C][C]0.76[/C][C]0.73[/C][C]0.6[/C][C]0.683[/C][C]0.605[/C][C]0.58[/C][C]0.21[/C][C]0.51[/C][C]0.59[/C][C]0.6[/C][C]0.38[/C][C]0.45[/C][C]0.51[/C][C]0.455[/C][C]0.48[/C][C]0.32[/C][C]0.365[/C][C]0.7[/C][C]0.723[/C][C]0.7[/C][C]0.528[/C][C]0.575[/C][C]0.89[/C][C]0.53[/C][C]0.58[/C][C]0.435[/C][C]0.46[/C][C]0.59[/C][C]0.407[/C][C]0.455[/C][C]0.667[/C][C]0.55[/C][C]0.655[/C][C]0.39[/C][C]0.47[/C][C]0.6[/C][C]0.89[/C][C]0.68[/C][C]0.712[/C][C]0.4[/C][C]0.54[/C][C]0.66[/C][C]0.705[/C][C]0.72[/C][C]0.535[/C][C]0.723[/C][C]0.597[/C][C]0.77[/C][C]0.525[/C][C]0.64[/C][C]0.695[/C][C]0.88[/C][C]0.59[/C][C]0.8[/C][C]0.42[/C][C]0.785[/C][C]0.633[/C][C]0.845[/C][C]0.07[/C][C]0.66[/C][C]0.93[/C][C]0.53[/C][C]0.648[/C][C]0[/C][C]0.67[/C][C]0.64[/C][C]0.85[/C][C]0.59[/C][C]0.73[/C][C]0.72[/C][C]0.41[/C][C]0.65[/C][C]0.67[/C][C]0.67[/C][C]0.78[/C][C]0.4[/C][C]0.487[/C][C]0.57[/C][C]0.765[/C][C]0.58[/C][C]0.66[/C][C]0.46[/C][C]0.607[/C][C]0.59[/C][C]0.645[/C][C]0.2[/C][C]0.66[/C][C]0.56[/C][C]0.315[/C][C]0.27[/C][C]0.6[/C][C]0.65[/C][C]0.62[/C][C]0.65[/C][C]0.58[/C][C]0.707[/C][C]0.07[/C][C]0.515[/C][C]0.51[/C][C]0.47[/C][C]0.483[/C][C]0.26[/C][C]0.86[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266254&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266254&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
Totaal ~ TOT
means0.440.880.5070.790.240.720.580.690.6570.5430.720.5730.740.690.5450.720.6250.480.6470.4050.510.5970.6450.480.520.580.50.710.6830.7030.8450.3550.570.650.4590.6350.5270.560.660.560.5550.5630.760.730.60.6830.6050.580.210.510.590.60.380.450.510.4550.480.320.3650.70.7230.70.5280.5750.890.530.580.4350.460.590.4070.4550.6670.550.6550.390.470.60.890.680.7120.40.540.660.7050.720.5350.7230.5970.770.5250.640.6950.880.590.80.420.7850.6330.8450.070.660.930.530.64800.670.640.850.590.730.720.410.650.670.670.780.40.4870.570.7650.580.660.460.6070.590.6450.20.660.560.3150.270.60.650.620.650.580.7070.070.5150.510.470.4830.260.86






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
TOT145105.1380.72524.6750
Residuals1424.1730.029 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
TOT & 145 & 105.138 & 0.725 & 24.675 & 0 \tabularnewline
Residuals & 142 & 4.173 & 0.029 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266254&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]TOT[/C][C]145[/C][C]105.138[/C][C]0.725[/C][C]24.675[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]142[/C][C]4.173[/C][C]0.029[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266254&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266254&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)
TOT145105.1380.72524.6750
Residuals1424.1730.029






Must Include Intercept to use Tukey Test 

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266254&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266254&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266254&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:

Must Include Intercept to use Tukey Test






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group1441.0670.35
142 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 144 & 1.067 & 0.35 \tabularnewline
  & 142 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266254&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]144[/C][C]1.067[/C][C]0.35[/C][/ROW]
[ROW][C] [/C][C]142[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266254&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266254&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)
Group1441.0670.35
142


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = FALSE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = FALSE ;
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')