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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 08:47:08 +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/t151306516081r4yoh2o5xybdf.htm/, Retrieved Wed, 15 May 2024 21:55:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309030, Retrieved Wed, 15 May 2024 21:55:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [2Anova ] [2017-12-12 07:47:08] [fda4350e119ddbaf0177fa3308cc9af4] [Current]
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Dataseries X:
1077	'AA'	'WDelay'
120	'AA'	'WDelay'
121	'AA'	'WeatherOK'
121	'AA'	'WeatherOK'
127	'AA'	'WeatherOK'
129	'AA'	'WeatherOK'
130	'AA'	'WeatherOK'
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'
152	'AA'	'WeatherOK'
158	'AA'	'WeatherOK'
159	'AA'	'WeatherOK'
161	'AA'	'WeatherOK'
189	'AA'	'WeatherOK'
190	'AA'	'WeatherOK'
192	'AA'	'WeatherOK'
200	'AA'	'WeatherOK'
208	'AA'	'WeatherOK'
208	'AA'	'WDelay'
216	'AA'	'WeatherOK'
222	'AA'	'WeatherOK'
242	'AA'	'WeatherOK'
249	'AA'	'WeatherOK'
290	'AA'	'WeatherOK'
305	'AA'	'WeatherOK'
306	'AA'	'WeatherOK'
344	'AA'	'WeatherOK'
610	'AA'	'WeatherOK'
741	'AA'	'WeatherOK'
782	'AA'	'WeatherOK'
120	'B6'	'WeatherOK'
124	'B6'	'WeatherOK'
124	'B6'	'WeatherOK'
125	'B6'	'WeatherOK'
126	'B6'	'WeatherOK'
127	'B6'	'WeatherOK'
128	'B6'	'WDelay'
131	'B6'	'WeatherOK'
133	'B6'	'WeatherOK'
135	'B6'	'WeatherOK'
135	'B6'	'WeatherOK'
137	'B6'	'WeatherOK'
139	'B6'	'WeatherOK'
140	'B6'	'WeatherOK'
142	'B6'	'WeatherOK'
142	'B6'	'WeatherOK'
143	'B6'	'WeatherOK'
145	'B6'	'WeatherOK'
147	'B6'	'WeatherOK'
148	'B6'	'WeatherOK'
150	'B6'	'WeatherOK'
153	'B6'	'WeatherOK'
154	'B6'	'WeatherOK'
157	'B6'	'WeatherOK'
158	'B6'	'WeatherOK'
175	'B6'	'WeatherOK'
178	'B6'	'WeatherOK'
178	'B6'	'WeatherOK'
190	'B6'	'WeatherOK'
191	'B6'	'WeatherOK'
192	'B6'	'WeatherOK'
192	'B6'	'WeatherOK'
193	'B6'	'WeatherOK'
195	'B6'	'WeatherOK'
195	'B6'	'WeatherOK'
207	'B6'	'WeatherOK'
218	'B6'	'WeatherOK'
219	'B6'	'WeatherOK'
224	'B6'	'WeatherOK'
227	'B6'	'WeatherOK'
228	'B6'	'WeatherOK'
234	'B6'	'WeatherOK'
234	'B6'	'WeatherOK'
242	'B6'	'WeatherOK'
244	'B6'	'WeatherOK'
259	'B6'	'WeatherOK'
273	'B6'	'WDelay'
286	'B6'	'WeatherOK'
291	'B6'	'WeatherOK'
343	'B6'	'WeatherOK'
568	'B6'	'WeatherOK'
134	'DL'	'WeatherOK'
134	'DL'	'WeatherOK'
138	'DL'	'WeatherOK'
140	'DL'	'WeatherOK'
142	'DL'	'WeatherOK'
144	'DL'	'WeatherOK'
155	'DL'	'WeatherOK'
167	'DL'	'WeatherOK'
177	'DL'	'WDelay'
179	'DL'	'WeatherOK'
179	'DL'	'WDelay'
182	'DL'	'WeatherOK'
210	'DL'	'WeatherOK'
224	'DL'	'WeatherOK'
248	'DL'	'WeatherOK'
273	'DL'	'WeatherOK'
293	'DL'	'WeatherOK'
410	'DL'	'WeatherOK'
430	'DL'	'WeatherOK'
452	'DL'	'WeatherOK'
454	'DL'	'WeatherOK'
520	'DL'	'WeatherOK'
586	'DL'	'WeatherOK'
617	'DL'	'WDelay'
659	'DL'	'WeatherOK'
759	'DL'	'WDelay'
924	'DL'	'WeatherOK'
941	'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=309030&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=309030&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309030&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
means468.333-267.833-35.333-241.905229.935148.03

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 468.333 & -267.833 & -35.333 & -241.905 & 229.935 & 148.03 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309030&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]468.333[/C][C]-267.833[/C][C]-35.333[/C][C]-241.905[/C][C]229.935[/C][C]148.03[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309030&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309030&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
means468.333-267.833-35.333-241.905229.935148.03







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A2483474.81241737.4057.9950.001
Treatment_B2126549.365126549.3654.1850.043
Treatment_A:Treatment_B265634.50632817.2531.0850.341
Residuals1113356392.56730237.771

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 483474.81 & 241737.405 & 7.995 & 0.001 \tabularnewline
Treatment_B & 2 & 126549.365 & 126549.365 & 4.185 & 0.043 \tabularnewline
Treatment_A:Treatment_B & 2 & 65634.506 & 32817.253 & 1.085 & 0.341 \tabularnewline
Residuals & 111 & 3356392.567 & 30237.771 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309030&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]483474.81[/C][C]241737.405[/C][C]7.995[/C][C]0.001[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]126549.365[/C][C]126549.365[/C][C]4.185[/C][C]0.043[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]65634.506[/C][C]32817.253[/C][C]1.085[/C][C]0.341[/C][/ROW]
[ROW][C]Residuals[/C][C]111[/C][C]3356392.567[/C][C]30237.771[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309030&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309030&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_A2483474.81241737.4057.9950.001
Treatment_B2126549.365126549.3654.1850.043
Treatment_A:Treatment_B265634.50632817.2531.0850.341
Residuals1113356392.56730237.771







Tukey Honest Significant Difference Comparisons
difflwruprp adj
B6-AA-56.526-145.0531.9970.287
DL-AA107.0094.127209.8920.039
DL-B6163.53666.375260.6960
WeatherOK-WDelay-121.969-241.517-2.420.046
B6:WDelay-AA:WDelay-267.833-728.196192.5290.543
DL:WDelay-AA:WDelay-35.333-420.5349.8331
AA:WeatherOK-AA:WDelay-241.905-545.28561.4760.198
B6:WeatherOK-AA:WDelay-279.803-579.74220.1370.082
DL:WeatherOK-AA:WDelay-129.208-438.029179.6120.829
DL:WDelay-B6:WDelay232.5-204.238669.2380.637
AA:WeatherOK-B6:WDelay25.929-340.713392.5711
B6:WeatherOK-B6:WDelay-11.969-375.769351.831
DL:WeatherOK-B6:WDelay138.625-232.531509.7810.887
AA:WeatherOK-DL:WDelay-206.571-472.74159.5980.223
B6:WeatherOK-DL:WDelay-244.469-506.7117.7710.083
DL:WeatherOK-DL:WDelay-93.875-366.229178.4790.917
B6:WeatherOK-AA:WeatherOK-37.898-149.50773.7110.922
DL:WeatherOK-AA:WeatherOK112.696-20.956246.3490.15
DL:WeatherOK-B6:WeatherOK150.59424.949276.240.009

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
B6-AA & -56.526 & -145.05 & 31.997 & 0.287 \tabularnewline
DL-AA & 107.009 & 4.127 & 209.892 & 0.039 \tabularnewline
DL-B6 & 163.536 & 66.375 & 260.696 & 0 \tabularnewline
WeatherOK-WDelay & -121.969 & -241.517 & -2.42 & 0.046 \tabularnewline
B6:WDelay-AA:WDelay & -267.833 & -728.196 & 192.529 & 0.543 \tabularnewline
DL:WDelay-AA:WDelay & -35.333 & -420.5 & 349.833 & 1 \tabularnewline
AA:WeatherOK-AA:WDelay & -241.905 & -545.285 & 61.476 & 0.198 \tabularnewline
B6:WeatherOK-AA:WDelay & -279.803 & -579.742 & 20.137 & 0.082 \tabularnewline
DL:WeatherOK-AA:WDelay & -129.208 & -438.029 & 179.612 & 0.829 \tabularnewline
DL:WDelay-B6:WDelay & 232.5 & -204.238 & 669.238 & 0.637 \tabularnewline
AA:WeatherOK-B6:WDelay & 25.929 & -340.713 & 392.571 & 1 \tabularnewline
B6:WeatherOK-B6:WDelay & -11.969 & -375.769 & 351.83 & 1 \tabularnewline
DL:WeatherOK-B6:WDelay & 138.625 & -232.531 & 509.781 & 0.887 \tabularnewline
AA:WeatherOK-DL:WDelay & -206.571 & -472.741 & 59.598 & 0.223 \tabularnewline
B6:WeatherOK-DL:WDelay & -244.469 & -506.71 & 17.771 & 0.083 \tabularnewline
DL:WeatherOK-DL:WDelay & -93.875 & -366.229 & 178.479 & 0.917 \tabularnewline
B6:WeatherOK-AA:WeatherOK & -37.898 & -149.507 & 73.711 & 0.922 \tabularnewline
DL:WeatherOK-AA:WeatherOK & 112.696 & -20.956 & 246.349 & 0.15 \tabularnewline
DL:WeatherOK-B6:WeatherOK & 150.594 & 24.949 & 276.24 & 0.009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309030&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]-56.526[/C][C]-145.05[/C][C]31.997[/C][C]0.287[/C][/ROW]
[ROW][C]DL-AA[/C][C]107.009[/C][C]4.127[/C][C]209.892[/C][C]0.039[/C][/ROW]
[ROW][C]DL-B6[/C][C]163.536[/C][C]66.375[/C][C]260.696[/C][C]0[/C][/ROW]
[ROW][C]WeatherOK-WDelay[/C][C]-121.969[/C][C]-241.517[/C][C]-2.42[/C][C]0.046[/C][/ROW]
[ROW][C]B6:WDelay-AA:WDelay[/C][C]-267.833[/C][C]-728.196[/C][C]192.529[/C][C]0.543[/C][/ROW]
[ROW][C]DL:WDelay-AA:WDelay[/C][C]-35.333[/C][C]-420.5[/C][C]349.833[/C][C]1[/C][/ROW]
[ROW][C]AA:WeatherOK-AA:WDelay[/C][C]-241.905[/C][C]-545.285[/C][C]61.476[/C][C]0.198[/C][/ROW]
[ROW][C]B6:WeatherOK-AA:WDelay[/C][C]-279.803[/C][C]-579.742[/C][C]20.137[/C][C]0.082[/C][/ROW]
[ROW][C]DL:WeatherOK-AA:WDelay[/C][C]-129.208[/C][C]-438.029[/C][C]179.612[/C][C]0.829[/C][/ROW]
[ROW][C]DL:WDelay-B6:WDelay[/C][C]232.5[/C][C]-204.238[/C][C]669.238[/C][C]0.637[/C][/ROW]
[ROW][C]AA:WeatherOK-B6:WDelay[/C][C]25.929[/C][C]-340.713[/C][C]392.571[/C][C]1[/C][/ROW]
[ROW][C]B6:WeatherOK-B6:WDelay[/C][C]-11.969[/C][C]-375.769[/C][C]351.83[/C][C]1[/C][/ROW]
[ROW][C]DL:WeatherOK-B6:WDelay[/C][C]138.625[/C][C]-232.531[/C][C]509.781[/C][C]0.887[/C][/ROW]
[ROW][C]AA:WeatherOK-DL:WDelay[/C][C]-206.571[/C][C]-472.741[/C][C]59.598[/C][C]0.223[/C][/ROW]
[ROW][C]B6:WeatherOK-DL:WDelay[/C][C]-244.469[/C][C]-506.71[/C][C]17.771[/C][C]0.083[/C][/ROW]
[ROW][C]DL:WeatherOK-DL:WDelay[/C][C]-93.875[/C][C]-366.229[/C][C]178.479[/C][C]0.917[/C][/ROW]
[ROW][C]B6:WeatherOK-AA:WeatherOK[/C][C]-37.898[/C][C]-149.507[/C][C]73.711[/C][C]0.922[/C][/ROW]
[ROW][C]DL:WeatherOK-AA:WeatherOK[/C][C]112.696[/C][C]-20.956[/C][C]246.349[/C][C]0.15[/C][/ROW]
[ROW][C]DL:WeatherOK-B6:WeatherOK[/C][C]150.594[/C][C]24.949[/C][C]276.24[/C][C]0.009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309030&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309030&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-AA-56.526-145.0531.9970.287
DL-AA107.0094.127209.8920.039
DL-B6163.53666.375260.6960
WeatherOK-WDelay-121.969-241.517-2.420.046
B6:WDelay-AA:WDelay-267.833-728.196192.5290.543
DL:WDelay-AA:WDelay-35.333-420.5349.8331
AA:WeatherOK-AA:WDelay-241.905-545.28561.4760.198
B6:WeatherOK-AA:WDelay-279.803-579.74220.1370.082
DL:WeatherOK-AA:WDelay-129.208-438.029179.6120.829
DL:WDelay-B6:WDelay232.5-204.238669.2380.637
AA:WeatherOK-B6:WDelay25.929-340.713392.5711
B6:WeatherOK-B6:WDelay-11.969-375.769351.831
DL:WeatherOK-B6:WDelay138.625-232.531509.7810.887
AA:WeatherOK-DL:WDelay-206.571-472.74159.5980.223
B6:WeatherOK-DL:WDelay-244.469-506.7117.7710.083
DL:WeatherOK-DL:WDelay-93.875-366.229178.4790.917
B6:WeatherOK-AA:WeatherOK-37.898-149.50773.7110.922
DL:WeatherOK-AA:WeatherOK112.696-20.956246.3490.15
DL:WeatherOK-B6:WeatherOK150.59424.949276.240.009







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group55.0420
111

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 5.042 & 0 \tabularnewline
  & 111 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309030&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]5.042[/C][C]0[/C][/ROW]
[ROW][C] [/C][C]111[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309030&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309030&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)
Group55.0420
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):
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')