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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_Two Factor ANOVA.wasp

Title produced by software

Two-Way ANOVA

Date of computation

Fri, 13 Dec 2019 14:51:31 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2019/Dec/13/t1576245287n5sn0t4qt2zgeey.htm/, Retrieved Sat, 18 May 2024 06:25:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=318968, Retrieved Sat, 18 May 2024 06:25:05 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

RatingBoontypeManVrouw

Estimated Impact

100

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Two-Way ANOVA] [Vrijdag13December...] [2019-12-13 13:51:31] [f84b1e954d04375f94c5bcb04f9ec7a1] [Current]

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Dataseries X:

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Histogram

Boxplots

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2.75 "'Forastero'" "'F'"
2.75 "'Trinitario'" "'M'"
2.75 "'Trinitario'" "'M'"
2.75 "'Trinitario'" "'M'"
3 "'Trinitario'" "'M'"
3 "'Trinitario'" "'M'"
3.25 "'Trinitario'" "'M'"
3.5 "'Trinitario'" "'F'"
3.5 "'Trinitario'" "'F'"
2.75 "'Trinitario'" "'M'"
3 "'Criollo'" "'M'"
2.75 "'Trinitario'" "'M'"
3.5 "'Trinitario'" "'M'"
2.5 "'Forastero'" "'F'"
2.5 "'Criollo'" "'F'"
2.75 "'Criollo'" "'F'"
3.25 "'Criollo'" "'F'"
2.75 "'Criollo'" "'F'"
3 "'Trinitario'" "'F'"
3 "'Trinitario'" "'F'"
3.25 "'Trinitario'" "'F'"
3 "'Criollo'" "'M'"
3.5 "'Trinitario'" "'M'"
3.25 "'Trinitario'" "'F'"
3.25 "'Trinitario'" "'M'"
3.5 "'Trinitario'" "'M'"
2.75 "'Trinitario'" "'M'"
3.5 "'Trinitario'" "'M'"
3.5 "'Trinitario'" "'F'"
3.25 "'Forastero'" "'F'"
3 "'Forastero'" "'F'"
3.5 "'Forastero'" "'F'"

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	Big 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318968&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]

2 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=318968&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318968&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	Big Analytics Cloud Computing Center

ANOVA Model
Response ~ Treatment_A * Treatment_B
means	3.262	-0.211	0.002	-0.038	0.152	0.002

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 3.262 & -0.211 & 0.002 & -0.038 & 0.152 & 0.002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318968&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]3.262[/C][C]-0.211[/C][C]0.002[/C][C]-0.038[/C][C]0.152[/C][C]0.002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=318968&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318968&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
Response ~ Treatment_A * Treatment_B
means	3.262	-0.211	0.002	-0.038	0.152	0.002

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
	2
Treatment_A	2	1.607	0.803	4.019	0.018
Treatment_B	2	0.044	0.044	0.222	0.638
Treatment_A:Treatment_B	2	0.417	0.208	1.042	0.353
Residuals	650	129.964	0.2

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 1.607 & 0.803 & 4.019 & 0.018 \tabularnewline
Treatment_B & 2 & 0.044 & 0.044 & 0.222 & 0.638 \tabularnewline
Treatment_A:Treatment_B & 2 & 0.417 & 0.208 & 1.042 & 0.353 \tabularnewline
Residuals & 650 & 129.964 & 0.2 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318968&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]Treatment_A[/C][C]2[/C][C]1.607[/C][C]0.803[/C][C]4.019[/C][C]0.018[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]0.044[/C][C]0.044[/C][C]0.222[/C][C]0.638[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]0.417[/C][C]0.208[/C][C]1.042[/C][C]0.353[/C][/ROW]
[ROW][C]Residuals[/C][C]650[/C][C]129.964[/C][C]0.2[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=318968&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318968&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
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
	2
Treatment_A	2	1.607	0.803	4.019	0.018
Treatment_B	2	0.044	0.044	0.222	0.638
Treatment_A:Treatment_B	2	0.417	0.208	1.042	0.353
Residuals	650	129.964	0.2

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
'Forastero'-'Criollo'	-0.144	-0.286	-0.003	0.044
'Trinitario'-'Criollo'	0.002	-0.098	0.101	0.999
'Trinitario'-'Forastero'	0.146	0.023	0.27	0.015
'M'-'F'	-0.017	-0.085	0.052	0.638
'Forastero':'F'-'Criollo':'F'	-0.211	-0.439	0.018	0.091
'Trinitario':'F'-'Criollo':'F'	0.002	-0.16	0.163	1
'Criollo':'M'-'Criollo':'F'	-0.038	-0.247	0.171	0.995
'Forastero':'M'-'Criollo':'F'	-0.097	-0.346	0.152	0.875
'Trinitario':'M'-'Criollo':'F'	-0.034	-0.2	0.132	0.992
'Trinitario':'F'-'Forastero':'F'	0.212	0.011	0.413	0.032
'Criollo':'M'-'Forastero':'F'	0.172	-0.069	0.413	0.318
'Forastero':'M'-'Forastero':'F'	0.113	-0.163	0.39	0.849
'Trinitario':'M'-'Forastero':'F'	0.176	-0.028	0.381	0.137
'Criollo':'M'-'Trinitario':'F'	-0.04	-0.218	0.139	0.988
'Forastero':'M'-'Trinitario':'F'	-0.099	-0.323	0.125	0.807
'Trinitario':'M'-'Trinitario':'F'	-0.036	-0.161	0.09	0.966
'Forastero':'M'-'Criollo':'M'	-0.059	-0.319	0.201	0.987
'Trinitario':'M'-'Criollo':'M'	0.004	-0.179	0.187	1
'Trinitario':'M'-'Forastero':'M'	0.063	-0.164	0.29	0.969

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
'Forastero'-'Criollo' & -0.144 & -0.286 & -0.003 & 0.044 \tabularnewline
'Trinitario'-'Criollo' & 0.002 & -0.098 & 0.101 & 0.999 \tabularnewline
'Trinitario'-'Forastero' & 0.146 & 0.023 & 0.27 & 0.015 \tabularnewline
'M'-'F' & -0.017 & -0.085 & 0.052 & 0.638 \tabularnewline
'Forastero':'F'-'Criollo':'F' & -0.211 & -0.439 & 0.018 & 0.091 \tabularnewline
'Trinitario':'F'-'Criollo':'F' & 0.002 & -0.16 & 0.163 & 1 \tabularnewline
'Criollo':'M'-'Criollo':'F' & -0.038 & -0.247 & 0.171 & 0.995 \tabularnewline
'Forastero':'M'-'Criollo':'F' & -0.097 & -0.346 & 0.152 & 0.875 \tabularnewline
'Trinitario':'M'-'Criollo':'F' & -0.034 & -0.2 & 0.132 & 0.992 \tabularnewline
'Trinitario':'F'-'Forastero':'F' & 0.212 & 0.011 & 0.413 & 0.032 \tabularnewline
'Criollo':'M'-'Forastero':'F' & 0.172 & -0.069 & 0.413 & 0.318 \tabularnewline
'Forastero':'M'-'Forastero':'F' & 0.113 & -0.163 & 0.39 & 0.849 \tabularnewline
'Trinitario':'M'-'Forastero':'F' & 0.176 & -0.028 & 0.381 & 0.137 \tabularnewline
'Criollo':'M'-'Trinitario':'F' & -0.04 & -0.218 & 0.139 & 0.988 \tabularnewline
'Forastero':'M'-'Trinitario':'F' & -0.099 & -0.323 & 0.125 & 0.807 \tabularnewline
'Trinitario':'M'-'Trinitario':'F' & -0.036 & -0.161 & 0.09 & 0.966 \tabularnewline
'Forastero':'M'-'Criollo':'M' & -0.059 & -0.319 & 0.201 & 0.987 \tabularnewline
'Trinitario':'M'-'Criollo':'M' & 0.004 & -0.179 & 0.187 & 1 \tabularnewline
'Trinitario':'M'-'Forastero':'M' & 0.063 & -0.164 & 0.29 & 0.969 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318968&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]'Forastero'-'Criollo'[/C][C]-0.144[/C][C]-0.286[/C][C]-0.003[/C][C]0.044[/C][/ROW]
[ROW][C]'Trinitario'-'Criollo'[/C][C]0.002[/C][C]-0.098[/C][C]0.101[/C][C]0.999[/C][/ROW]
[ROW][C]'Trinitario'-'Forastero'[/C][C]0.146[/C][C]0.023[/C][C]0.27[/C][C]0.015[/C][/ROW]
[ROW][C]'M'-'F'[/C][C]-0.017[/C][C]-0.085[/C][C]0.052[/C][C]0.638[/C][/ROW]
[ROW][C]'Forastero':'F'-'Criollo':'F'[/C][C]-0.211[/C][C]-0.439[/C][C]0.018[/C][C]0.091[/C][/ROW]
[ROW][C]'Trinitario':'F'-'Criollo':'F'[/C][C]0.002[/C][C]-0.16[/C][C]0.163[/C][C]1[/C][/ROW]
[ROW][C]'Criollo':'M'-'Criollo':'F'[/C][C]-0.038[/C][C]-0.247[/C][C]0.171[/C][C]0.995[/C][/ROW]
[ROW][C]'Forastero':'M'-'Criollo':'F'[/C][C]-0.097[/C][C]-0.346[/C][C]0.152[/C][C]0.875[/C][/ROW]
[ROW][C]'Trinitario':'M'-'Criollo':'F'[/C][C]-0.034[/C][C]-0.2[/C][C]0.132[/C][C]0.992[/C][/ROW]
[ROW][C]'Trinitario':'F'-'Forastero':'F'[/C][C]0.212[/C][C]0.011[/C][C]0.413[/C][C]0.032[/C][/ROW]
[ROW][C]'Criollo':'M'-'Forastero':'F'[/C][C]0.172[/C][C]-0.069[/C][C]0.413[/C][C]0.318[/C][/ROW]
[ROW][C]'Forastero':'M'-'Forastero':'F'[/C][C]0.113[/C][C]-0.163[/C][C]0.39[/C][C]0.849[/C][/ROW]
[ROW][C]'Trinitario':'M'-'Forastero':'F'[/C][C]0.176[/C][C]-0.028[/C][C]0.381[/C][C]0.137[/C][/ROW]
[ROW][C]'Criollo':'M'-'Trinitario':'F'[/C][C]-0.04[/C][C]-0.218[/C][C]0.139[/C][C]0.988[/C][/ROW]
[ROW][C]'Forastero':'M'-'Trinitario':'F'[/C][C]-0.099[/C][C]-0.323[/C][C]0.125[/C][C]0.807[/C][/ROW]
[ROW][C]'Trinitario':'M'-'Trinitario':'F'[/C][C]-0.036[/C][C]-0.161[/C][C]0.09[/C][C]0.966[/C][/ROW]
[ROW][C]'Forastero':'M'-'Criollo':'M'[/C][C]-0.059[/C][C]-0.319[/C][C]0.201[/C][C]0.987[/C][/ROW]
[ROW][C]'Trinitario':'M'-'Criollo':'M'[/C][C]0.004[/C][C]-0.179[/C][C]0.187[/C][C]1[/C][/ROW]
[ROW][C]'Trinitario':'M'-'Forastero':'M'[/C][C]0.063[/C][C]-0.164[/C][C]0.29[/C][C]0.969[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=318968&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318968&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
	diff	lwr	upr	p adj
'Forastero'-'Criollo'	-0.144	-0.286	-0.003	0.044
'Trinitario'-'Criollo'	0.002	-0.098	0.101	0.999
'Trinitario'-'Forastero'	0.146	0.023	0.27	0.015
'M'-'F'	-0.017	-0.085	0.052	0.638
'Forastero':'F'-'Criollo':'F'	-0.211	-0.439	0.018	0.091
'Trinitario':'F'-'Criollo':'F'	0.002	-0.16	0.163	1
'Criollo':'M'-'Criollo':'F'	-0.038	-0.247	0.171	0.995
'Forastero':'M'-'Criollo':'F'	-0.097	-0.346	0.152	0.875
'Trinitario':'M'-'Criollo':'F'	-0.034	-0.2	0.132	0.992
'Trinitario':'F'-'Forastero':'F'	0.212	0.011	0.413	0.032
'Criollo':'M'-'Forastero':'F'	0.172	-0.069	0.413	0.318
'Forastero':'M'-'Forastero':'F'	0.113	-0.163	0.39	0.849
'Trinitario':'M'-'Forastero':'F'	0.176	-0.028	0.381	0.137
'Criollo':'M'-'Trinitario':'F'	-0.04	-0.218	0.139	0.988
'Forastero':'M'-'Trinitario':'F'	-0.099	-0.323	0.125	0.807
'Trinitario':'M'-'Trinitario':'F'	-0.036	-0.161	0.09	0.966
'Forastero':'M'-'Criollo':'M'	-0.059	-0.319	0.201	0.987
'Trinitario':'M'-'Criollo':'M'	0.004	-0.179	0.187	1
'Trinitario':'M'-'Forastero':'M'	0.063	-0.164	0.29	0.969

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	5	2.942	0.012
	650

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 2.942 & 0.012 \tabularnewline
  & 650 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=318968&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]2.942[/C][C]0.012[/C][/ROW]
[ROW][C] [/C][C]650[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=318968&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318968&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
	Df	F value	Pr(>F)
Group	5	2.942	0.012
	650

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par2 = grey ; par3 = FALSE ; par4 = Unknown ;

Parameters (R input):

par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;

R code (references can be found in the software module):

par4 <- 'Unknown'
par3 <- '3'
par2 <- '2'
par1 <- '1'
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])
names(xdf)<-c('Response', 'Treatment_A', 'Treatment_B')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment_A * Treatment_B- 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment_A * Treatment_B, 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$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, lmxdf$call['formula'],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$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
for(i in 1 : length(rownames(anova.xdf))-1){
a<-table.row.start(a)
a<-table.element(a,rownames(anova.xdf)[i] ,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[i], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[i], 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$'Df'[i+1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[i+1], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment_A + Treatment_B, data=xdf, xlab=V2, ylab=V1, main='Boxplots of ANOVA Groups')
dev.off()
bitmap(file='designplot.png')
xdf2 <- xdf # to preserve xdf make copy for function
names(xdf2) <- c(V1, V2, V3)
plot.design(xdf2, main='Design Plot of Group Means')
dev.off()
bitmap(file='interactionplot.png')
interaction.plot(xdf$Treatment_A, xdf$Treatment_B, xdf$Response, 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(1,2,3,3), 2,2))
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,round(thsd[[nt]][i,j], digits=3), 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<-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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code