FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSat, 10 Dec 2016 15:15:38 +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/10/t14813797098y0enx0wx94m88n.htm/, Retrieved Mon, 06 May 2024 05:03:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298687, Retrieved Mon, 06 May 2024 05:03:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact46

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 EP ...] [2016-12-10 14:15:38] [462f83e9ca944f1b841aaa868aea0854] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9	15
11	18
13	21
11	NA
12	NA
11	19
8	NA
12	NA
13	NA
12	20
12	20
11	18
12	20
10	17
12	20
12	20
NA	NA
NA	NA
8	NA
13	NA
11	18
11	NA
11	18
11	NA
13	NA
11	NA
12	20
11	18
12	20
12	20
10	16
11	19
12	20
11	NA
9	16
12	20
11	NA
11	19
12	20
13	22
11	NA
12	20
9	15
12	20
11	18
12	20
12	NA
NA	7
10	16
3	NA
12	20
13	NA
13	NA
9	15
11	18
11	18
NA	NA
12	19
12	20
11	NA
12	20
11	18
12	19
11	18
11	18
8	14
12	20
NA	7
12	20
11	18
11	NA
11	NA
10	NA
10	NA
13	NA
11	18
11	19
11	18
13	22
12	20
12	NA
9	15
12	NA
12	20
13	NA
15	25
13	22
13	22
11	NA
12	20
9	14
11	NA
13	21
12	NA
13	21
11	NA
12	20
14	23
13	22
11	18
4	NA
13	NA
11	18
11	18
11	NA
13	NA
12	NA
12	NA
11	NA
12	20
12	NA
10	NA
11	NA
9	15
9	NA
12	20
11	18
13	NA
11	18
11	18
11	18
11	18
12	NA
11	18
13	NA
11	18
11	18
12	NA
11	NA
11	NA
9	15
8	NA
14	23
10	NA
9	15
8	NA
14	24
NA	NA
11	18
14	23
13	21
10	NA
11	18
8	NA
10	16
13	21
12	20
14	23
10	17
12	NA
9	NA
12	20
11	18
11	18
10	16
11	NA
12	20
10	NA
11	NA
13	22
11	18
NA	8
12	20
11	NA
NA	NA
10	NA
12	20
10	NA
13	22

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298687&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]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298687&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298687&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 time3 seconds
R ServerBig Analytics Cloud Computing Center






ANOVA Model
TVDCSUM ~ EPSUM
means16.3331.7843.6045.256.8678.667-2.333-1.333-9

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
TVDCSUM  ~  EPSUM \tabularnewline
means & 16.333 & 1.784 & 3.604 & 5.25 & 6.867 & 8.667 & -2.333 & -1.333 & -9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298687&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]TVDCSUM  ~  EPSUM[/C][/ROW]
[ROW][C]means[/C][C]16.333[/C][C]1.784[/C][C]3.604[/C][C]5.25[/C][C]6.867[/C][C]8.667[/C][C]-2.333[/C][C]-1.333[/C][C]-9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298687&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298687&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
TVDCSUM ~ EPSUM
means16.3331.7843.6045.256.8678.667-2.333-1.333-9






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
EPSUM8867.656108.457776.9910
Residuals9413.1210.14 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
EPSUM & 8 & 867.656 & 108.457 & 776.991 & 0 \tabularnewline
Residuals & 94 & 13.121 & 0.14 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298687&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]EPSUM[/C][C]8[/C][C]867.656[/C][C]108.457[/C][C]776.991[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]94[/C][C]13.121[/C][C]0.14[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298687&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298687&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)
EPSUM8867.656108.457776.9910
Residuals9413.1210.14






Tukey Honest Significant Difference Comparisons
difflwruprp adj
11-101.7841.2592.310
12-103.6043.0764.1320
13-105.254.6575.8430
14-106.8676.1487.5850
15-108.6677.3859.9480
8-10-2.333-3.615-1.0520
9-10-1.333-1.959-0.7080
NA-10-9-9.839-8.1610
12-111.821.5282.1120
13-113.4663.0673.8640
14-115.0824.5145.6510
15-116.8825.6798.0860
8-11-4.118-5.321-2.9140
9-11-3.118-3.562-2.6730
NA-11-10.784-11.499-10.070
13-121.6461.2442.0470
14-123.2622.6923.8330
15-125.0633.8586.2670
8-12-5.938-7.142-4.7330
9-12-4.938-5.385-4.490
NA-12-12.604-13.32-11.8880
14-131.6170.9852.2480
15-133.4172.1824.6510
8-13-7.583-8.818-6.3490
9-13-6.583-7.106-6.060
NA-13-14.25-15.016-13.4840
15-141.80.53.10.001
8-14-9.2-10.5-7.90
9-14-8.2-8.862-7.5380
NA-14-15.867-16.733-150
8-15-11-12.678-9.3220
9-15-10-11.25-8.750
NA-15-17.667-19.037-16.2970
9-81-0.252.250.227
NA-8-6.667-8.037-5.2970
NA-9-7.667-8.458-6.8760

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
11-10 & 1.784 & 1.259 & 2.31 & 0 \tabularnewline
12-10 & 3.604 & 3.076 & 4.132 & 0 \tabularnewline
13-10 & 5.25 & 4.657 & 5.843 & 0 \tabularnewline
14-10 & 6.867 & 6.148 & 7.585 & 0 \tabularnewline
15-10 & 8.667 & 7.385 & 9.948 & 0 \tabularnewline
8-10 & -2.333 & -3.615 & -1.052 & 0 \tabularnewline
9-10 & -1.333 & -1.959 & -0.708 & 0 \tabularnewline
NA-10 & -9 & -9.839 & -8.161 & 0 \tabularnewline
12-11 & 1.82 & 1.528 & 2.112 & 0 \tabularnewline
13-11 & 3.466 & 3.067 & 3.864 & 0 \tabularnewline
14-11 & 5.082 & 4.514 & 5.651 & 0 \tabularnewline
15-11 & 6.882 & 5.679 & 8.086 & 0 \tabularnewline
8-11 & -4.118 & -5.321 & -2.914 & 0 \tabularnewline
9-11 & -3.118 & -3.562 & -2.673 & 0 \tabularnewline
NA-11 & -10.784 & -11.499 & -10.07 & 0 \tabularnewline
13-12 & 1.646 & 1.244 & 2.047 & 0 \tabularnewline
14-12 & 3.262 & 2.692 & 3.833 & 0 \tabularnewline
15-12 & 5.063 & 3.858 & 6.267 & 0 \tabularnewline
8-12 & -5.938 & -7.142 & -4.733 & 0 \tabularnewline
9-12 & -4.938 & -5.385 & -4.49 & 0 \tabularnewline
NA-12 & -12.604 & -13.32 & -11.888 & 0 \tabularnewline
14-13 & 1.617 & 0.985 & 2.248 & 0 \tabularnewline
15-13 & 3.417 & 2.182 & 4.651 & 0 \tabularnewline
8-13 & -7.583 & -8.818 & -6.349 & 0 \tabularnewline
9-13 & -6.583 & -7.106 & -6.06 & 0 \tabularnewline
NA-13 & -14.25 & -15.016 & -13.484 & 0 \tabularnewline
15-14 & 1.8 & 0.5 & 3.1 & 0.001 \tabularnewline
8-14 & -9.2 & -10.5 & -7.9 & 0 \tabularnewline
9-14 & -8.2 & -8.862 & -7.538 & 0 \tabularnewline
NA-14 & -15.867 & -16.733 & -15 & 0 \tabularnewline
8-15 & -11 & -12.678 & -9.322 & 0 \tabularnewline
9-15 & -10 & -11.25 & -8.75 & 0 \tabularnewline
NA-15 & -17.667 & -19.037 & -16.297 & 0 \tabularnewline
9-8 & 1 & -0.25 & 2.25 & 0.227 \tabularnewline
NA-8 & -6.667 & -8.037 & -5.297 & 0 \tabularnewline
NA-9 & -7.667 & -8.458 & -6.876 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298687&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]1.784[/C][C]1.259[/C][C]2.31[/C][C]0[/C][/ROW]
[ROW][C]12-10[/C][C]3.604[/C][C]3.076[/C][C]4.132[/C][C]0[/C][/ROW]
[ROW][C]13-10[/C][C]5.25[/C][C]4.657[/C][C]5.843[/C][C]0[/C][/ROW]
[ROW][C]14-10[/C][C]6.867[/C][C]6.148[/C][C]7.585[/C][C]0[/C][/ROW]
[ROW][C]15-10[/C][C]8.667[/C][C]7.385[/C][C]9.948[/C][C]0[/C][/ROW]
[ROW][C]8-10[/C][C]-2.333[/C][C]-3.615[/C][C]-1.052[/C][C]0[/C][/ROW]
[ROW][C]9-10[/C][C]-1.333[/C][C]-1.959[/C][C]-0.708[/C][C]0[/C][/ROW]
[ROW][C]NA-10[/C][C]-9[/C][C]-9.839[/C][C]-8.161[/C][C]0[/C][/ROW]
[ROW][C]12-11[/C][C]1.82[/C][C]1.528[/C][C]2.112[/C][C]0[/C][/ROW]
[ROW][C]13-11[/C][C]3.466[/C][C]3.067[/C][C]3.864[/C][C]0[/C][/ROW]
[ROW][C]14-11[/C][C]5.082[/C][C]4.514[/C][C]5.651[/C][C]0[/C][/ROW]
[ROW][C]15-11[/C][C]6.882[/C][C]5.679[/C][C]8.086[/C][C]0[/C][/ROW]
[ROW][C]8-11[/C][C]-4.118[/C][C]-5.321[/C][C]-2.914[/C][C]0[/C][/ROW]
[ROW][C]9-11[/C][C]-3.118[/C][C]-3.562[/C][C]-2.673[/C][C]0[/C][/ROW]
[ROW][C]NA-11[/C][C]-10.784[/C][C]-11.499[/C][C]-10.07[/C][C]0[/C][/ROW]
[ROW][C]13-12[/C][C]1.646[/C][C]1.244[/C][C]2.047[/C][C]0[/C][/ROW]
[ROW][C]14-12[/C][C]3.262[/C][C]2.692[/C][C]3.833[/C][C]0[/C][/ROW]
[ROW][C]15-12[/C][C]5.063[/C][C]3.858[/C][C]6.267[/C][C]0[/C][/ROW]
[ROW][C]8-12[/C][C]-5.938[/C][C]-7.142[/C][C]-4.733[/C][C]0[/C][/ROW]
[ROW][C]9-12[/C][C]-4.938[/C][C]-5.385[/C][C]-4.49[/C][C]0[/C][/ROW]
[ROW][C]NA-12[/C][C]-12.604[/C][C]-13.32[/C][C]-11.888[/C][C]0[/C][/ROW]
[ROW][C]14-13[/C][C]1.617[/C][C]0.985[/C][C]2.248[/C][C]0[/C][/ROW]
[ROW][C]15-13[/C][C]3.417[/C][C]2.182[/C][C]4.651[/C][C]0[/C][/ROW]
[ROW][C]8-13[/C][C]-7.583[/C][C]-8.818[/C][C]-6.349[/C][C]0[/C][/ROW]
[ROW][C]9-13[/C][C]-6.583[/C][C]-7.106[/C][C]-6.06[/C][C]0[/C][/ROW]
[ROW][C]NA-13[/C][C]-14.25[/C][C]-15.016[/C][C]-13.484[/C][C]0[/C][/ROW]
[ROW][C]15-14[/C][C]1.8[/C][C]0.5[/C][C]3.1[/C][C]0.001[/C][/ROW]
[ROW][C]8-14[/C][C]-9.2[/C][C]-10.5[/C][C]-7.9[/C][C]0[/C][/ROW]
[ROW][C]9-14[/C][C]-8.2[/C][C]-8.862[/C][C]-7.538[/C][C]0[/C][/ROW]
[ROW][C]NA-14[/C][C]-15.867[/C][C]-16.733[/C][C]-15[/C][C]0[/C][/ROW]
[ROW][C]8-15[/C][C]-11[/C][C]-12.678[/C][C]-9.322[/C][C]0[/C][/ROW]
[ROW][C]9-15[/C][C]-10[/C][C]-11.25[/C][C]-8.75[/C][C]0[/C][/ROW]
[ROW][C]NA-15[/C][C]-17.667[/C][C]-19.037[/C][C]-16.297[/C][C]0[/C][/ROW]
[ROW][C]9-8[/C][C]1[/C][C]-0.25[/C][C]2.25[/C][C]0.227[/C][/ROW]
[ROW][C]NA-8[/C][C]-6.667[/C][C]-8.037[/C][C]-5.297[/C][C]0[/C][/ROW]
[ROW][C]NA-9[/C][C]-7.667[/C][C]-8.458[/C][C]-6.876[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298687&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298687&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
11-101.7841.2592.310
12-103.6043.0764.1320
13-105.254.6575.8430
14-106.8676.1487.5850
15-108.6677.3859.9480
8-10-2.333-3.615-1.0520
9-10-1.333-1.959-0.7080
NA-10-9-9.839-8.1610
12-111.821.5282.1120
13-113.4663.0673.8640
14-115.0824.5145.6510
15-116.8825.6798.0860
8-11-4.118-5.321-2.9140
9-11-3.118-3.562-2.6730
NA-11-10.784-11.499-10.070
13-121.6461.2442.0470
14-123.2622.6923.8330
15-125.0633.8586.2670
8-12-5.938-7.142-4.7330
9-12-4.938-5.385-4.490
NA-12-12.604-13.32-11.8880
14-131.6170.9852.2480
15-133.4172.1824.6510
8-13-7.583-8.818-6.3490
9-13-6.583-7.106-6.060
NA-13-14.25-15.016-13.4840
15-141.80.53.10.001
8-14-9.2-10.5-7.90
9-14-8.2-8.862-7.5380
NA-14-15.867-16.733-150
8-15-11-12.678-9.3220
9-15-10-11.25-8.750
NA-15-17.667-19.037-16.2970
9-81-0.252.250.227
NA-8-6.667-8.037-5.2970
NA-9-7.667-8.458-6.8760






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group81.4070.204
94 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 8 & 1.407 & 0.204 \tabularnewline
  & 94 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298687&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]1.407[/C][C]0.204[/C][/ROW]
[ROW][C] [/C][C]94[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298687&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298687&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)
Group81.4070.204
94


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 8 ; par2 = 0 ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
R code (references can be found in the software module):
par3 <- 'TRUE'
par2 <- '2'
par1 <- '1'
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')