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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, 12 Dec 2017 09:36:22 +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/2017/Dec/12/t1513067834i3qsvxdvy5n9v41.htm/, Retrieved Wed, 15 May 2024 11:56:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309037, Retrieved Wed, 15 May 2024 11:56:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [anova 2 way ] [2017-12-12 08:36:22] [fda4350e119ddbaf0177fa3308cc9af4] [Current]
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Dataseries X:
127	'AA'	'WDelay'
129	'AA'	'WDelay'
131	'AA'	'WeatherOK'
132	'AA'	'WeatherOK'
132	'AA'	'WeatherOK'
136	'AA'	'WeatherOK'
137	'AA'	'WeatherOK'
137	'AA'	'WeatherOK'
141	'AA'	'WeatherOK'
142	'AA'	'WeatherOK'
144	'AA'	'WeatherOK'
149	'AA'	'WeatherOK'
158	'AA'	'WeatherOK'
159	'AA'	'WeatherOK'
190	'AA'	'WeatherOK'
192	'AA'	'WeatherOK'
208	'AA'	'WeatherOK'
216	'AA'	'WeatherOK'
242	'AA'	'WeatherOK'
249	'AA'	'WeatherOK'
290	'AA'	'WeatherOK'
306	'AA'	'WeatherOK'
610	'AA'	'WeatherOK'
782	'AA'	'WeatherOK'
120	'AA'	'WeatherOK'
126	'AA'	'WeatherOK'
133	'AA'	'WDelay'
135	'AA'	'WeatherOK'
142	'AA'	'WeatherOK'
145	'AA'	'WeatherOK'
191	'AA'	'WeatherOK'
192	'AA'	'WeatherOK'
228	'AA'	'WeatherOK'
244	'AA'	'WeatherOK'
343	'AA'	'WeatherOK'
134	'AA'	'WeatherOK'
138	'AA'	'WeatherOK'
140	'AA'	'WeatherOK'
142	'B6'	'WeatherOK'
155	'B6'	'WeatherOK'
179	'B6'	'WeatherOK'
179	'B6'	'WeatherOK'
293	'B6'	'WeatherOK'
430	'B6'	'WeatherOK'
659	'B6'	'WDelay'
924	'B6'	'WeatherOK'
133.00	'B6'	'WeatherOK'
135.00	'B6'	'WeatherOK'
135.00	'B6'	'WeatherOK'
137.00	'B6'	'WeatherOK'
139.00	'B6'	'WeatherOK'
140.00	'B6'	'WeatherOK'
142.00	'B6'	'WeatherOK'
142.00	'B6'	'WeatherOK'
143.00	'B6'	'WeatherOK'
145.00	'B6'	'WeatherOK'
147.00	'B6'	'WeatherOK'
148.00	'B6'	'WeatherOK'
150.00	'B6'	'WeatherOK'
153.00	'B6'	'WeatherOK'
154.00	'B6'	'WeatherOK'
157.00	'B6'	'WeatherOK'
158.00	'B6'	'WeatherOK'
175.00	'B6'	'WeatherOK'
178.00	'B6'	'WeatherOK'
178.00	'B6'	'WeatherOK'
190.00	'B6'	'WeatherOK'
191.00	'B6'	'WeatherOK'
192.00	'B6'	'WeatherOK'
192.00	'B6'	'WeatherOK'
193.00	'B6'	'WeatherOK'
195.00	'B6'	'WeatherOK'
195.00	'B6'	'WeatherOK'
207.00	'B6'	'WeatherOK'
218.00	'B6'	'WeatherOK'
219.00	'B6'	'WeatherOK'
224.00	'B6'	'WeatherOK'
227.00	'B6'	'WeatherOK'
228.00	'B6'	'WeatherOK'
234.00	'B6'	'WeatherOK'
234.00	'B6'	'WeatherOK'
242.00	'B6'	'WeatherOK'
244.00	'B6'	'WeatherOK'
259.00	'B6'	'WeatherOK'
273.00	'B6'	'WDelay'
286.00	'B6'	'WeatherOK'
291.00	'B6'	'WeatherOK'
343.00	'B6'	'WeatherOK'
568.00	'B6'	'WeatherOK'
134.00	'DL'	'WeatherOK'
134.00	'DL'	'WeatherOK'
138.00	'DL'	'WeatherOK'
140.00	'DL'	'WeatherOK'
142.00	'DL'	'WeatherOK'
144.00	'DL'	'WeatherOK'
155.00	'DL'	'WeatherOK'
167.00	'DL'	'WeatherOK'
177.00	'DL'	'WDelay'
179.00	'DL'	'WeatherOK'
179.00	'DL'	'WDelay'
182.00	'DL'	'WeatherOK'
210.00	'DL'	'WeatherOK'
224.00	'DL'	'WeatherOK'
248.00	'DL'	'WeatherOK'
273.00	'DL'	'WeatherOK'
293.00	'DL'	'WeatherOK'
410.00	'DL'	'WeatherOK'
430.00	'DL'	'WeatherOK'
452.00	'DL'	'WeatherOK'
454.00	'DL'	'WeatherOK'
520.00	'DL'	'WeatherOK'
586.00	'DL'	'WeatherOK'
617.00	'DL'	'WDelay'
659.00	'DL'	'WeatherOK'
759.00	'DL'	'WDelay'
924.00	'DL'	'WeatherOK'
941.00	'DL'	'WeatherOK'




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309037&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]4 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309037&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309037&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 Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center







ANOVA Model
Response ~ Treatment_A * Treatment_B
means129.667336.333303.33377.79-326.178-171.665

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 129.667 & 336.333 & 303.333 & 77.79 & -326.178 & -171.665 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309037&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]129.667[/C][C]336.333[/C][C]303.333[/C][C]77.79[/C][C]-326.178[/C][C]-171.665[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309037&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309037&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
means129.667336.333303.33377.79-326.178-171.665







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A2410449.708205224.8547.2820.001
Treatment_B242066.02442066.0241.4930.224
Treatment_A:Treatment_B2123423.18861711.5942.190.117
Residuals1113128391.6128183.708

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 410449.708 & 205224.854 & 7.282 & 0.001 \tabularnewline
Treatment_B & 2 & 42066.024 & 42066.024 & 1.493 & 0.224 \tabularnewline
Treatment_A:Treatment_B & 2 & 123423.188 & 61711.594 & 2.19 & 0.117 \tabularnewline
Residuals & 111 & 3128391.61 & 28183.708 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309037&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]410449.708[/C][C]205224.854[/C][C]7.282[/C][C]0.001[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]42066.024[/C][C]42066.024[/C][C]1.493[/C][C]0.224[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]123423.188[/C][C]61711.594[/C][C]2.19[/C][C]0.117[/C][/ROW]
[ROW][C]Residuals[/C][C]111[/C][C]3128391.61[/C][C]28183.708[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309037&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309037&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
Treatment_A2410449.708205224.8547.2820.001
Treatment_B242066.02442066.0241.4930.224
Treatment_A:Treatment_B2123423.18861711.5942.190.117
Residuals1113128391.6128183.708







Tukey Honest Significant Difference Comparisons
difflwruprp adj
B6-AA26.037-59.427111.5010.75
DL-AA151.2251.893250.5470.001
DL-B6125.18331.38218.9850.006
WeatherOK-WDelay-70.321-185.73745.0960.23
B6:WDelay-AA:WDelay336.333-108.118780.7840.249
DL:WDelay-AA:WDelay303.333-68.521675.1880.178
AA:WeatherOK-AA:WDelay77.79-215.104370.6850.972
B6:WeatherOK-AA:WDelay87.946-201.627377.5180.95
DL:WeatherOK-AA:WDelay209.458-88.688507.6050.328
DL:WDelay-B6:WDelay-33-454.643388.6431
AA:WeatherOK-B6:WDelay-258.543-612.51395.4270.286
B6:WeatherOK-B6:WDelay-248.388-599.614102.8380.321
DL:WeatherOK-B6:WDelay-126.875-485.203231.4530.908
AA:WeatherOK-DL:WDelay-225.543-482.51331.4270.12
B6:WeatherOK-DL:WDelay-215.388-468.56537.7890.143
DL:WeatherOK-DL:WDelay-93.875-356.816169.0660.905
B6:WeatherOK-AA:WeatherOK10.155-97.596117.9061
DL:WeatherOK-AA:WeatherOK131.6682.635260.7010.043
DL:WeatherOK-B6:WeatherOK121.5130.21242.8160.049

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
B6-AA & 26.037 & -59.427 & 111.501 & 0.75 \tabularnewline
DL-AA & 151.22 & 51.893 & 250.547 & 0.001 \tabularnewline
DL-B6 & 125.183 & 31.38 & 218.985 & 0.006 \tabularnewline
WeatherOK-WDelay & -70.321 & -185.737 & 45.096 & 0.23 \tabularnewline
B6:WDelay-AA:WDelay & 336.333 & -108.118 & 780.784 & 0.249 \tabularnewline
DL:WDelay-AA:WDelay & 303.333 & -68.521 & 675.188 & 0.178 \tabularnewline
AA:WeatherOK-AA:WDelay & 77.79 & -215.104 & 370.685 & 0.972 \tabularnewline
B6:WeatherOK-AA:WDelay & 87.946 & -201.627 & 377.518 & 0.95 \tabularnewline
DL:WeatherOK-AA:WDelay & 209.458 & -88.688 & 507.605 & 0.328 \tabularnewline
DL:WDelay-B6:WDelay & -33 & -454.643 & 388.643 & 1 \tabularnewline
AA:WeatherOK-B6:WDelay & -258.543 & -612.513 & 95.427 & 0.286 \tabularnewline
B6:WeatherOK-B6:WDelay & -248.388 & -599.614 & 102.838 & 0.321 \tabularnewline
DL:WeatherOK-B6:WDelay & -126.875 & -485.203 & 231.453 & 0.908 \tabularnewline
AA:WeatherOK-DL:WDelay & -225.543 & -482.513 & 31.427 & 0.12 \tabularnewline
B6:WeatherOK-DL:WDelay & -215.388 & -468.565 & 37.789 & 0.143 \tabularnewline
DL:WeatherOK-DL:WDelay & -93.875 & -356.816 & 169.066 & 0.905 \tabularnewline
B6:WeatherOK-AA:WeatherOK & 10.155 & -97.596 & 117.906 & 1 \tabularnewline
DL:WeatherOK-AA:WeatherOK & 131.668 & 2.635 & 260.701 & 0.043 \tabularnewline
DL:WeatherOK-B6:WeatherOK & 121.513 & 0.21 & 242.816 & 0.049 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309037&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]B6-AA[/C][C]26.037[/C][C]-59.427[/C][C]111.501[/C][C]0.75[/C][/ROW]
[ROW][C]DL-AA[/C][C]151.22[/C][C]51.893[/C][C]250.547[/C][C]0.001[/C][/ROW]
[ROW][C]DL-B6[/C][C]125.183[/C][C]31.38[/C][C]218.985[/C][C]0.006[/C][/ROW]
[ROW][C]WeatherOK-WDelay[/C][C]-70.321[/C][C]-185.737[/C][C]45.096[/C][C]0.23[/C][/ROW]
[ROW][C]B6:WDelay-AA:WDelay[/C][C]336.333[/C][C]-108.118[/C][C]780.784[/C][C]0.249[/C][/ROW]
[ROW][C]DL:WDelay-AA:WDelay[/C][C]303.333[/C][C]-68.521[/C][C]675.188[/C][C]0.178[/C][/ROW]
[ROW][C]AA:WeatherOK-AA:WDelay[/C][C]77.79[/C][C]-215.104[/C][C]370.685[/C][C]0.972[/C][/ROW]
[ROW][C]B6:WeatherOK-AA:WDelay[/C][C]87.946[/C][C]-201.627[/C][C]377.518[/C][C]0.95[/C][/ROW]
[ROW][C]DL:WeatherOK-AA:WDelay[/C][C]209.458[/C][C]-88.688[/C][C]507.605[/C][C]0.328[/C][/ROW]
[ROW][C]DL:WDelay-B6:WDelay[/C][C]-33[/C][C]-454.643[/C][C]388.643[/C][C]1[/C][/ROW]
[ROW][C]AA:WeatherOK-B6:WDelay[/C][C]-258.543[/C][C]-612.513[/C][C]95.427[/C][C]0.286[/C][/ROW]
[ROW][C]B6:WeatherOK-B6:WDelay[/C][C]-248.388[/C][C]-599.614[/C][C]102.838[/C][C]0.321[/C][/ROW]
[ROW][C]DL:WeatherOK-B6:WDelay[/C][C]-126.875[/C][C]-485.203[/C][C]231.453[/C][C]0.908[/C][/ROW]
[ROW][C]AA:WeatherOK-DL:WDelay[/C][C]-225.543[/C][C]-482.513[/C][C]31.427[/C][C]0.12[/C][/ROW]
[ROW][C]B6:WeatherOK-DL:WDelay[/C][C]-215.388[/C][C]-468.565[/C][C]37.789[/C][C]0.143[/C][/ROW]
[ROW][C]DL:WeatherOK-DL:WDelay[/C][C]-93.875[/C][C]-356.816[/C][C]169.066[/C][C]0.905[/C][/ROW]
[ROW][C]B6:WeatherOK-AA:WeatherOK[/C][C]10.155[/C][C]-97.596[/C][C]117.906[/C][C]1[/C][/ROW]
[ROW][C]DL:WeatherOK-AA:WeatherOK[/C][C]131.668[/C][C]2.635[/C][C]260.701[/C][C]0.043[/C][/ROW]
[ROW][C]DL:WeatherOK-B6:WeatherOK[/C][C]121.513[/C][C]0.21[/C][C]242.816[/C][C]0.049[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309037&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309037&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
B6-AA26.037-59.427111.5010.75
DL-AA151.2251.893250.5470.001
DL-B6125.18331.38218.9850.006
WeatherOK-WDelay-70.321-185.73745.0960.23
B6:WDelay-AA:WDelay336.333-108.118780.7840.249
DL:WDelay-AA:WDelay303.333-68.521675.1880.178
AA:WeatherOK-AA:WDelay77.79-215.104370.6850.972
B6:WeatherOK-AA:WDelay87.946-201.627377.5180.95
DL:WeatherOK-AA:WDelay209.458-88.688507.6050.328
DL:WDelay-B6:WDelay-33-454.643388.6431
AA:WeatherOK-B6:WDelay-258.543-612.51395.4270.286
B6:WeatherOK-B6:WDelay-248.388-599.614102.8380.321
DL:WeatherOK-B6:WDelay-126.875-485.203231.4530.908
AA:WeatherOK-DL:WDelay-225.543-482.51331.4270.12
B6:WeatherOK-DL:WDelay-215.388-468.56537.7890.143
DL:WeatherOK-DL:WDelay-93.875-356.816169.0660.905
B6:WeatherOK-AA:WeatherOK10.155-97.596117.9061
DL:WeatherOK-AA:WeatherOK131.6682.635260.7010.043
DL:WeatherOK-B6:WeatherOK121.5130.21242.8160.049







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group53.970.002
111

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 3.97 & 0.002 \tabularnewline
  & 111 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309037&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]3.97[/C][C]0.002[/C][/ROW]
[ROW][C] [/C][C]111[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309037&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309037&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)
Group53.970.002
111



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 3 ; par4 = TRUE ;
R code (references can be found in the software module):
par4 <- 'FALSE'
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<-levene.test(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')