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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, 29 Nov 2011 04:56:03 -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/Nov/29/t132256059458pvnc4lg7skcrz.htm/, Retrieved Fri, 29 Mar 2024 06:03:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148145, Retrieved Fri, 29 Mar 2024 06:03:10 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [] [2011-11-29 09:56:03] [87b6e955a128bfb8d1e350b3ce0d281e] [Current]
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Dataseries X:
1	'WWE'	0
0	'WWE'	0
1	'WWE'	2
1	'WWE'	0
1	'WWE'	2
0	'WWE'	1
0	'WWE'	0
1	'WWE'	2
0	'WWE'	0
1	'WWE'	0
0	'WWE'	0
0	'WWE'	0
1	'WWE'	0
0	'WWE'	NA
0	'WWE'	1
0	'WWE'	NA
1	'WWE'	-1
1	'WWE'	0
0	'WWE'	1
1	'WWE'	1
0	'WWE'	0
1	'WWE'	0
1	'WWE'	0
0	'WWE'	1
0	'WWE'	2
0	'WWE'	2
0	'WWE'	0
1	'WWE'	0
1	'WWE'	1
0	'WWE'	1
1	'WWE'	1
0	'WWE'	1
1	'WWE'	1
0	'WWE'	0
1	'WWE'	0
1	'WWE'	0
0	'WWE'	0
0	'WWE'	0
0	'WWE'	NA
1	'WWE'	1
0	'WWE'	0
1	'CSWE'	0
0	'CSWE'	NA
0	'CSWE'	0
1	'CSWE'	NA
1	'CSWE'	1
1	'CSWE'	0
0	'CSWE'	0
1	'CSWE'	1
0	'CSWE'	0
0	'CSWE'	0
1	'CSWE'	1
0	'CSWE'	1
0	'CSWE'	0
1	'CSWE'	NA
1	'CSWE'	1
1	'CSWE'	NA
1	'CSWE'	0
1	'CSWE'	1
0	'CSWE'	NA
0	'CSWE'	1
1	'CSWE'	0
0	'CSWE'	NA
1	'CSWE'	0
0	'CSWE'	1
0	'CSWE'	0
1	'CSWE'	1
1	'CSWE'	1
1	'CSWE'	1
0	'CSWE'	0
1	'CSWE'	1
0	'CSWE'	2
1	'CSWE'	1
0	'CSWE'	NA
1	'CSWE'	0
1	'CSWE'	NA
0	'CSWE'	0
0	'CSWE'	0
0	'CSWE'	0
1	'CSWE'	1
0	'CSWE'	1
0	'C'	0
1	'C'	1
1	'C'	-1
1	'C'	1
0	'C'	NA
1	'C'	0
0	'C'	0
1	'C'	1
0	'C'	0
1	'C'	NA
0	'C'	0
1	'C'	1
1	'C'	1
1	'C'	0
1	'C'	0
1	'C'	0
1	'C'	0
1	'C'	NA
0	'C'	0
0	'C'	1
1	'C'	0
0	'C'	1
0	'C'	0
0	'C'	0
1	'C'	0
1	'C'	0
0	'C'	0
1	'C'	0
1	'C'	0
0	'C'	0
1	'C'	0
0	'C'	1
1	'C'	0
0	'C'	0
1	'C'	0
0	'C'	1
1	'C'	0
0	'C'	NA
0	'C'	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148145&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148145&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148145&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







ANOVA Model
xdf2$score ~ xdf2$geslacht * xdf2$methode
names(Intercept)xdf2$geslacht1xdf2$methodeCSWExdf2$methodeWWExdf2$geslacht1:xdf2$methodeCSWExdf2$geslacht1:xdf2$methodeWWE
means0.26667-0.0666670.133330.259650.313730.066667

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
xdf2$score ~ xdf2$geslacht * xdf2$methode \tabularnewline
names & (Intercept) & xdf2$geslacht1 & xdf2$methodeCSWE & xdf2$methodeWWE & xdf2$geslacht1:xdf2$methodeCSWE & xdf2$geslacht1:xdf2$methodeWWE \tabularnewline
means & 0.26667 & -0.066667 & 0.13333 & 0.25965 & 0.31373 & 0.066667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148145&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]xdf2$score ~ xdf2$geslacht * xdf2$methode[/C][/ROW]
[ROW][C]names[/C][C](Intercept)[/C][C]xdf2$geslacht1[/C][C]xdf2$methodeCSWE[/C][C]xdf2$methodeWWE[/C][C]xdf2$geslacht1:xdf2$methodeCSWE[/C][C]xdf2$geslacht1:xdf2$methodeWWE[/C][/ROW]
[ROW][C]means[/C][C]0.26667[/C][C]-0.066667[/C][C]0.13333[/C][C]0.25965[/C][C]0.31373[/C][C]0.066667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148145&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148145&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$score ~ xdf2$geslacht * xdf2$methode
names(Intercept)xdf2$geslacht1xdf2$methodeCSWExdf2$methodeWWExdf2$geslacht1:xdf2$methodeCSWExdf2$geslacht1:xdf2$methodeWWE
means0.26667-0.0666670.133330.259650.313730.066667







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
xdf2$geslacht10.0382650.0382650.0969130.75622
xdf2$methode12.13711.06862.70630.071724
xdf2$geslacht:xdf2$methode10.449510.224760.569230.5678
Residuals9939.0890.39484

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
xdf2$geslacht & 1 & 0.038265 & 0.038265 & 0.096913 & 0.75622 \tabularnewline
xdf2$methode & 1 & 2.1371 & 1.0686 & 2.7063 & 0.071724 \tabularnewline
xdf2$geslacht:xdf2$methode & 1 & 0.44951 & 0.22476 & 0.56923 & 0.5678 \tabularnewline
Residuals & 99 & 39.089 & 0.39484 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148145&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]1[/C][C][/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]xdf2$geslacht[/C][C]1[/C][C]0.038265[/C][C]0.038265[/C][C]0.096913[/C][C]0.75622[/C][/ROW]
[ROW][C]xdf2$methode[/C][C]1[/C][C]2.1371[/C][C]1.0686[/C][C]2.7063[/C][C]0.071724[/C][/ROW]
[ROW][C]xdf2$geslacht:xdf2$methode[/C][C]1[/C][C]0.44951[/C][C]0.22476[/C][C]0.56923[/C][C]0.5678[/C][/ROW]
[ROW][C]Residuals[/C][C]99[/C][C]39.089[/C][C]0.39484[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148145&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148145&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)
1
xdf2$geslacht10.0382650.0382650.0969130.75622
xdf2$methode12.13711.06862.70630.071724
xdf2$geslacht:xdf2$methode10.449510.224760.569230.5678
Residuals9939.0890.39484







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.038265-0.205630.282160.75622
CSWE-C0.30422-0.0614810.669910.12264
WWE-C0.30048-0.0498130.650770.10782
WWE-CSWE-0.0037384-0.362470.3550.99966
1:C-0:C-0.066667-0.690440.55710.9996
0:CSWE-0:C0.13333-0.533510.800170.99207
1:CSWE-0:C0.38039-0.266541.02730.52929
0:WWE-0:C0.25965-0.371120.890420.83763
1:WWE-0:C0.25965-0.371120.890420.83763
0:CSWE-1:C0.2-0.423770.823770.93732
1:CSWE-1:C0.44706-0.155381.04950.26755
0:WWE-1:C0.32632-0.258730.911370.58678
1:WWE-1:C0.32632-0.258730.911370.58678
1:CSWE-0:CSWE0.24706-0.399870.893990.87622
0:WWE-0:CSWE0.12632-0.504450.757080.99201
1:WWE-0:CSWE0.12632-0.504450.757080.99201
0:WWE-1:CSWE-0.12074-0.730420.488940.99241
1:WWE-1:CSWE-0.12074-0.730420.488940.99241
1:WWE-0:WWE0-0.59250.59251

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 0.038265 & -0.20563 & 0.28216 & 0.75622 \tabularnewline
CSWE-C & 0.30422 & -0.061481 & 0.66991 & 0.12264 \tabularnewline
WWE-C & 0.30048 & -0.049813 & 0.65077 & 0.10782 \tabularnewline
WWE-CSWE & -0.0037384 & -0.36247 & 0.355 & 0.99966 \tabularnewline
1:C-0:C & -0.066667 & -0.69044 & 0.5571 & 0.9996 \tabularnewline
0:CSWE-0:C & 0.13333 & -0.53351 & 0.80017 & 0.99207 \tabularnewline
1:CSWE-0:C & 0.38039 & -0.26654 & 1.0273 & 0.52929 \tabularnewline
0:WWE-0:C & 0.25965 & -0.37112 & 0.89042 & 0.83763 \tabularnewline
1:WWE-0:C & 0.25965 & -0.37112 & 0.89042 & 0.83763 \tabularnewline
0:CSWE-1:C & 0.2 & -0.42377 & 0.82377 & 0.93732 \tabularnewline
1:CSWE-1:C & 0.44706 & -0.15538 & 1.0495 & 0.26755 \tabularnewline
0:WWE-1:C & 0.32632 & -0.25873 & 0.91137 & 0.58678 \tabularnewline
1:WWE-1:C & 0.32632 & -0.25873 & 0.91137 & 0.58678 \tabularnewline
1:CSWE-0:CSWE & 0.24706 & -0.39987 & 0.89399 & 0.87622 \tabularnewline
0:WWE-0:CSWE & 0.12632 & -0.50445 & 0.75708 & 0.99201 \tabularnewline
1:WWE-0:CSWE & 0.12632 & -0.50445 & 0.75708 & 0.99201 \tabularnewline
0:WWE-1:CSWE & -0.12074 & -0.73042 & 0.48894 & 0.99241 \tabularnewline
1:WWE-1:CSWE & -0.12074 & -0.73042 & 0.48894 & 0.99241 \tabularnewline
1:WWE-0:WWE & 0 & -0.5925 & 0.5925 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148145&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]1-0[/C][C]0.038265[/C][C]-0.20563[/C][C]0.28216[/C][C]0.75622[/C][/ROW]
[ROW][C]CSWE-C[/C][C]0.30422[/C][C]-0.061481[/C][C]0.66991[/C][C]0.12264[/C][/ROW]
[ROW][C]WWE-C[/C][C]0.30048[/C][C]-0.049813[/C][C]0.65077[/C][C]0.10782[/C][/ROW]
[ROW][C]WWE-CSWE[/C][C]-0.0037384[/C][C]-0.36247[/C][C]0.355[/C][C]0.99966[/C][/ROW]
[ROW][C]1:C-0:C[/C][C]-0.066667[/C][C]-0.69044[/C][C]0.5571[/C][C]0.9996[/C][/ROW]
[ROW][C]0:CSWE-0:C[/C][C]0.13333[/C][C]-0.53351[/C][C]0.80017[/C][C]0.99207[/C][/ROW]
[ROW][C]1:CSWE-0:C[/C][C]0.38039[/C][C]-0.26654[/C][C]1.0273[/C][C]0.52929[/C][/ROW]
[ROW][C]0:WWE-0:C[/C][C]0.25965[/C][C]-0.37112[/C][C]0.89042[/C][C]0.83763[/C][/ROW]
[ROW][C]1:WWE-0:C[/C][C]0.25965[/C][C]-0.37112[/C][C]0.89042[/C][C]0.83763[/C][/ROW]
[ROW][C]0:CSWE-1:C[/C][C]0.2[/C][C]-0.42377[/C][C]0.82377[/C][C]0.93732[/C][/ROW]
[ROW][C]1:CSWE-1:C[/C][C]0.44706[/C][C]-0.15538[/C][C]1.0495[/C][C]0.26755[/C][/ROW]
[ROW][C]0:WWE-1:C[/C][C]0.32632[/C][C]-0.25873[/C][C]0.91137[/C][C]0.58678[/C][/ROW]
[ROW][C]1:WWE-1:C[/C][C]0.32632[/C][C]-0.25873[/C][C]0.91137[/C][C]0.58678[/C][/ROW]
[ROW][C]1:CSWE-0:CSWE[/C][C]0.24706[/C][C]-0.39987[/C][C]0.89399[/C][C]0.87622[/C][/ROW]
[ROW][C]0:WWE-0:CSWE[/C][C]0.12632[/C][C]-0.50445[/C][C]0.75708[/C][C]0.99201[/C][/ROW]
[ROW][C]1:WWE-0:CSWE[/C][C]0.12632[/C][C]-0.50445[/C][C]0.75708[/C][C]0.99201[/C][/ROW]
[ROW][C]0:WWE-1:CSWE[/C][C]-0.12074[/C][C]-0.73042[/C][C]0.48894[/C][C]0.99241[/C][/ROW]
[ROW][C]1:WWE-1:CSWE[/C][C]-0.12074[/C][C]-0.73042[/C][C]0.48894[/C][C]0.99241[/C][/ROW]
[ROW][C]1:WWE-0:WWE[/C][C]0[/C][C]-0.5925[/C][C]0.5925[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148145&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148145&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
1-00.038265-0.205630.282160.75622
CSWE-C0.30422-0.0614810.669910.12264
WWE-C0.30048-0.0498130.650770.10782
WWE-CSWE-0.0037384-0.362470.3550.99966
1:C-0:C-0.066667-0.690440.55710.9996
0:CSWE-0:C0.13333-0.533510.800170.99207
1:CSWE-0:C0.38039-0.266541.02730.52929
0:WWE-0:C0.25965-0.371120.890420.83763
1:WWE-0:C0.25965-0.371120.890420.83763
0:CSWE-1:C0.2-0.423770.823770.93732
1:CSWE-1:C0.44706-0.155381.04950.26755
0:WWE-1:C0.32632-0.258730.911370.58678
1:WWE-1:C0.32632-0.258730.911370.58678
1:CSWE-0:CSWE0.24706-0.399870.893990.87622
0:WWE-0:CSWE0.12632-0.504450.757080.99201
1:WWE-0:CSWE0.12632-0.504450.757080.99201
0:WWE-1:CSWE-0.12074-0.730420.488940.99241
1:WWE-1:CSWE-0.12074-0.730420.488940.99241
1:WWE-0:WWE0-0.59250.59251







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group50.98980.42799
99

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 0.9898 & 0.42799 \tabularnewline
  & 99 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148145&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]0.9898[/C][C]0.42799[/C][/ROW]
[ROW][C] [/C][C]99[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148145&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148145&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)
Group50.98980.42799
99



Parameters (Session):
Parameters (R input):
par1 = 3 ; par2 = 1 ; par3 = 2 ; 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')