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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 computationTue, 20 Dec 2011 07:14:07 -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/2011/Dec/20/t13243832739ax06fvxr4jzm70.htm/, Retrieved Thu, 31 Oct 2024 23:46:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157943, Retrieved Thu, 31 Oct 2024 23:46:03 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [D1 2Anova] [2011-12-20 09:12:14] [0f81819b439c6e991d1a2004e9982756]
- R  D    [Two-Way ANOVA] [D1 2Anova] [2011-12-20 12:14:07] [cdf03f2f7d2bbe3f2da091606ae8e03f] [Current]
-    D      [Two-Way ANOVA] [D1 2Anova] [2011-12-20 12:23:21] [0f81819b439c6e991d1a2004e9982756]
-    D        [Two-Way ANOVA] [paper (7)] [2012-12-12 21:44:20] [300ac07a477d84a470eebba12c2af4b2]
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Dataseries X:
'M'	'G1'	18
'M'	'G2'	21
'M'	'G3'	28
'M'	'G2'	35
'M'	'G1'	33
'M'	'G1'	32
'M'	'G2'	32
'M'	'G3'	22
'M'	'G1'	34
'M'	'G1'	20
'M'	'G2'	18
'M'	'G3'	35
'M'	'G1'	22
'M'	'G1'	30
'M'	'G1'	17
'M'	'G1'	33
'F'	'G2'	20
'F'	'G3'	26
'F'	'G2'	26
'F'	'G3'	21
'F'	'G1'	27
'F'	'G2'	17
'F'	'G3'	27
'F'	'G1'	17
'F'	'G1'	27
'F'	'G2'	26
'F'	'G3'	25
'F'	'G1'	23
'F'	'G2'	20
'F'	'G3'	16
'F'	'G1'	26
'F'	'G2'	29
'F'	'G3'	16




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157943&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157943&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157943&T=0

As an alternative you can also use a 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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







ANOVA Model
xdf2$Som ~ xdf2$Groep * xdf2$Geslacht
names(Intercept)xdf2$GroepG2xdf2$GroepG3xdf2$GeslachtMxdf2$GroepG2:xdf2$GeslachtMxdf2$GroepG3:xdf2$GeslachtM
means24-1-2.16672.55560.944443.9444

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
xdf2$Som ~ xdf2$Groep * xdf2$Geslacht \tabularnewline
names & (Intercept) & xdf2$GroepG2 & xdf2$GroepG3 & xdf2$GeslachtM & xdf2$GroepG2:xdf2$GeslachtM & xdf2$GroepG3:xdf2$GeslachtM \tabularnewline
means & 24 & -1 & -2.1667 & 2.5556 & 0.94444 & 3.9444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157943&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]xdf2$Som ~ xdf2$Groep * xdf2$Geslacht[/C][/ROW]
[ROW][C]names[/C][C](Intercept)[/C][C]xdf2$GroepG2[/C][C]xdf2$GroepG3[/C][C]xdf2$GeslachtM[/C][C]xdf2$GroepG2:xdf2$GeslachtM[/C][C]xdf2$GroepG3:xdf2$GeslachtM[/C][/ROW]
[ROW][C]means[/C][C]24[/C][C]-1[/C][C]-2.1667[/C][C]2.5556[/C][C]0.94444[/C][C]3.9444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157943&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157943&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Model
xdf2$Som ~ xdf2$Groep * xdf2$Geslacht
names(Intercept)xdf2$GroepG2xdf2$GroepG3xdf2$GeslachtMxdf2$GroepG2:xdf2$GeslachtMxdf2$GroepG3:xdf2$GeslachtM
means24-1-2.16672.55560.944443.9444







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
xdf2$Groep217.2958.64740.233310.79349
xdf2$Geslacht2115.18115.183.10760.089246
xdf2$Groep:xdf2$Geslacht219.7139.85650.265930.76847
Residuals271000.737.064

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
xdf2$Groep & 2 & 17.295 & 8.6474 & 0.23331 & 0.79349 \tabularnewline
xdf2$Geslacht & 2 & 115.18 & 115.18 & 3.1076 & 0.089246 \tabularnewline
xdf2$Groep:xdf2$Geslacht & 2 & 19.713 & 9.8565 & 0.26593 & 0.76847 \tabularnewline
Residuals & 27 & 1000.7 & 37.064 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157943&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]2[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]xdf2$Groep[/C][C]2[/C][C]17.295[/C][C]8.6474[/C][C]0.23331[/C][C]0.79349[/C][/ROW]
[ROW][C]xdf2$Geslacht[/C][C]2[/C][C]115.18[/C][C]115.18[/C][C]3.1076[/C][C]0.089246[/C][/ROW]
[ROW][C]xdf2$Groep:xdf2$Geslacht[/C][C]2[/C][C]19.713[/C][C]9.8565[/C][C]0.26593[/C][C]0.76847[/C][/ROW]
[ROW][C]Residuals[/C][C]27[/C][C]1000.7[/C][C]37.064[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157943&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157943&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
xdf2$Groep217.2958.64740.233310.79349
xdf2$Geslacht2115.18115.183.10760.089246
xdf2$Groep:xdf2$Geslacht219.7139.85650.265930.76847
Residuals271000.737.064







Tukey Honest Significant Difference Comparisons
difflwruprp adj
G2-G1-1.2429-7.49275.00690.8752
G3-G1-1.6429-8.0924.80630.80415
G3-G2-0.4-7.33556.53550.98879
M-F3.5929-0.758097.94390.10171
G2:F-G1:F-1-12.29510.2950.99978
G3:F-G1:F-2.1667-13.4619.12810.99103
G1:M-G1:F2.5556-7.848412.960.97307
G2:M-G1:F2.5-10.01315.0130.9892
G3:M-G1:F4.3333-9.288717.9550.92202
G3:F-G2:F-1.1667-11.9369.60250.9994
G1:M-G2:F3.5556-6.275313.3860.87375
G2:M-G2:F3.5-8.540315.540.9455
G3:M-G2:F5.3333-7.856118.5230.81402
G1:M-G3:F4.7222-5.108614.5530.68427
G2:M-G3:F4.6667-7.373616.7070.83886
G3:M-G3:F6.5-6.689519.6890.6611
G2:M-G1:M-0.055556-11.26411.1531
G3:M-G1:M1.7778-10.65714.2130.99772
G3:M-G2:M1.8333-12.41316.080.99862

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
G2-G1 & -1.2429 & -7.4927 & 5.0069 & 0.8752 \tabularnewline
G3-G1 & -1.6429 & -8.092 & 4.8063 & 0.80415 \tabularnewline
G3-G2 & -0.4 & -7.3355 & 6.5355 & 0.98879 \tabularnewline
M-F & 3.5929 & -0.75809 & 7.9439 & 0.10171 \tabularnewline
G2:F-G1:F & -1 & -12.295 & 10.295 & 0.99978 \tabularnewline
G3:F-G1:F & -2.1667 & -13.461 & 9.1281 & 0.99103 \tabularnewline
G1:M-G1:F & 2.5556 & -7.8484 & 12.96 & 0.97307 \tabularnewline
G2:M-G1:F & 2.5 & -10.013 & 15.013 & 0.9892 \tabularnewline
G3:M-G1:F & 4.3333 & -9.2887 & 17.955 & 0.92202 \tabularnewline
G3:F-G2:F & -1.1667 & -11.936 & 9.6025 & 0.9994 \tabularnewline
G1:M-G2:F & 3.5556 & -6.2753 & 13.386 & 0.87375 \tabularnewline
G2:M-G2:F & 3.5 & -8.5403 & 15.54 & 0.9455 \tabularnewline
G3:M-G2:F & 5.3333 & -7.8561 & 18.523 & 0.81402 \tabularnewline
G1:M-G3:F & 4.7222 & -5.1086 & 14.553 & 0.68427 \tabularnewline
G2:M-G3:F & 4.6667 & -7.3736 & 16.707 & 0.83886 \tabularnewline
G3:M-G3:F & 6.5 & -6.6895 & 19.689 & 0.6611 \tabularnewline
G2:M-G1:M & -0.055556 & -11.264 & 11.153 & 1 \tabularnewline
G3:M-G1:M & 1.7778 & -10.657 & 14.213 & 0.99772 \tabularnewline
G3:M-G2:M & 1.8333 & -12.413 & 16.08 & 0.99862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157943&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]G2-G1[/C][C]-1.2429[/C][C]-7.4927[/C][C]5.0069[/C][C]0.8752[/C][/ROW]
[ROW][C]G3-G1[/C][C]-1.6429[/C][C]-8.092[/C][C]4.8063[/C][C]0.80415[/C][/ROW]
[ROW][C]G3-G2[/C][C]-0.4[/C][C]-7.3355[/C][C]6.5355[/C][C]0.98879[/C][/ROW]
[ROW][C]M-F[/C][C]3.5929[/C][C]-0.75809[/C][C]7.9439[/C][C]0.10171[/C][/ROW]
[ROW][C]G2:F-G1:F[/C][C]-1[/C][C]-12.295[/C][C]10.295[/C][C]0.99978[/C][/ROW]
[ROW][C]G3:F-G1:F[/C][C]-2.1667[/C][C]-13.461[/C][C]9.1281[/C][C]0.99103[/C][/ROW]
[ROW][C]G1:M-G1:F[/C][C]2.5556[/C][C]-7.8484[/C][C]12.96[/C][C]0.97307[/C][/ROW]
[ROW][C]G2:M-G1:F[/C][C]2.5[/C][C]-10.013[/C][C]15.013[/C][C]0.9892[/C][/ROW]
[ROW][C]G3:M-G1:F[/C][C]4.3333[/C][C]-9.2887[/C][C]17.955[/C][C]0.92202[/C][/ROW]
[ROW][C]G3:F-G2:F[/C][C]-1.1667[/C][C]-11.936[/C][C]9.6025[/C][C]0.9994[/C][/ROW]
[ROW][C]G1:M-G2:F[/C][C]3.5556[/C][C]-6.2753[/C][C]13.386[/C][C]0.87375[/C][/ROW]
[ROW][C]G2:M-G2:F[/C][C]3.5[/C][C]-8.5403[/C][C]15.54[/C][C]0.9455[/C][/ROW]
[ROW][C]G3:M-G2:F[/C][C]5.3333[/C][C]-7.8561[/C][C]18.523[/C][C]0.81402[/C][/ROW]
[ROW][C]G1:M-G3:F[/C][C]4.7222[/C][C]-5.1086[/C][C]14.553[/C][C]0.68427[/C][/ROW]
[ROW][C]G2:M-G3:F[/C][C]4.6667[/C][C]-7.3736[/C][C]16.707[/C][C]0.83886[/C][/ROW]
[ROW][C]G3:M-G3:F[/C][C]6.5[/C][C]-6.6895[/C][C]19.689[/C][C]0.6611[/C][/ROW]
[ROW][C]G2:M-G1:M[/C][C]-0.055556[/C][C]-11.264[/C][C]11.153[/C][C]1[/C][/ROW]
[ROW][C]G3:M-G1:M[/C][C]1.7778[/C][C]-10.657[/C][C]14.213[/C][C]0.99772[/C][/ROW]
[ROW][C]G3:M-G2:M[/C][C]1.8333[/C][C]-12.413[/C][C]16.08[/C][C]0.99862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157943&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157943&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
G2-G1-1.2429-7.49275.00690.8752
G3-G1-1.6429-8.0924.80630.80415
G3-G2-0.4-7.33556.53550.98879
M-F3.5929-0.758097.94390.10171
G2:F-G1:F-1-12.29510.2950.99978
G3:F-G1:F-2.1667-13.4619.12810.99103
G1:M-G1:F2.5556-7.848412.960.97307
G2:M-G1:F2.5-10.01315.0130.9892
G3:M-G1:F4.3333-9.288717.9550.92202
G3:F-G2:F-1.1667-11.9369.60250.9994
G1:M-G2:F3.5556-6.275313.3860.87375
G2:M-G2:F3.5-8.540315.540.9455
G3:M-G2:F5.3333-7.856118.5230.81402
G1:M-G3:F4.7222-5.108614.5530.68427
G2:M-G3:F4.6667-7.373616.7070.83886
G3:M-G3:F6.5-6.689519.6890.6611
G2:M-G1:M-0.055556-11.26411.1531
G3:M-G1:M1.7778-10.65714.2130.99772
G3:M-G2:M1.8333-12.41316.080.99862







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group51.08140.39281
27

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 1.0814 & 0.39281 \tabularnewline
  & 27 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157943&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]1.0814[/C][C]0.39281[/C][/ROW]
[ROW][C] [/C][C]27[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157943&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157943&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group51.08140.39281
27



Parameters (Session):
par1 = 3 ; par2 = 2 ; par3 = 1 ; par4 = TRUE ;
Parameters (R input):
par1 = 3 ; par2 = 2 ; par3 = 1 ; 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])
mynames<- c(V1, V2, V3)
xdf2<-xdf
names(xdf2)<-mynames
names(xdf)<-c('R', 'A', 'B')
mynames <- c(V1, V2, V3)
if(intercept == FALSE)eval (substitute(lmout<-lm(xdf$R ~ xdf$A * xdf$B- 1, data = xdf), list(xdf=quote(xdf2),R=mynames[1],A=mynames[2],B=mynames[3]) ))else eval(substitute(lmout<-lm(xdf$R ~ xdf$A * xdf$B, data = xdf), list(xdf=quote(xdf2),R=mynames[1],A=mynames[2],B=mynames[3]) ))
oldnames<-names(lmout$coeff)
newnames<-gsub('xdf2$', '', oldnames)
(names(lmout$coeff)<-newnames)
(names(lmout$coefficients)<-newnames)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmout$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
callstr<-gsub('xdf2$', '',as.character(lmout$call$formula))
callstr<-paste(callstr[2], callstr[1], callstr[3])
a<-table.element(a,callstr ,length(lmout$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'names',,TRUE)
for(i in 1:length(lmout$coefficients)){
a<-table.element(a, names(lmout$coefficients[i]),,FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmout$coefficients)){
a<-table.element(a, signif(lmout$coefficients[i], digits=5),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
(aov.xdf<-aov(lmout) )
(anova.xdf<-anova(lmout) )
rownames(anova.xdf)<-gsub('xdf2$','',rownames(anova.xdf))
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$Df[1],,FALSE)
a<-table.element(a, signif(anova.xdf$'Sum Sq'[i], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'Mean Sq'[i], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'F value'[i], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'Pr(>F)'[i], digits=5),,FALSE)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$'Df'[i+1],,FALSE)
a<-table.element(a, signif(anova.xdf$'Sum Sq'[i+1], digits=5),,FALSE)
a<-table.element(a, signif(anova.xdf$'Mean Sq'[i+1], digits=5),,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(R ~ A + 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$A, xdf$B, xdf$R, 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(0,0,1,2,1,2,0,0,3,3,3,3), 2,6))
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,signif(thsd[[nt]][i,j], digits=5), 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(lmout)
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,signif(lt.lmxdf[[i]][1], digits=5), 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')