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Description of Statistical Computation

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 computationMon, 28 Nov 2011 12:22:56 -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/28/t1322501153v09fnykfm4b4ef1.htm/, Retrieved Sat, 20 Apr 2024 06:28:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147905, Retrieved Sat, 20 Apr 2024 06:28:03 +0000
QR Codes:

Original text written by user:Artificial data for demonstration of ANOVA
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact951

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variability] [Two-Way ANOVA] [2010-11-30 21:42:30] [74be16979710d4c4e7c6647856088456]
- RM      [Two-Way ANOVA] [Two-Way ANOVA - C...] [2011-11-28 17:22:56] [a9208f4f8d3b118336aae915785f2bd9] [Current]
- R         [Two-Way ANOVA] [ANOVA Week 9] [2011-12-01 12:02:11] [0e3849a58d2010f680210bfa36dadcb4]
- R         [Two-Way ANOVA] [] [2011-12-01 12:02:56] [483074838c7eb9e0ff7f7d3e3c3f8586]
- R         [Two-Way ANOVA] [Question i] [2011-12-01 12:10:19] [57084a6890c0bc671c16163e98194e4e]
- R         [Two-Way ANOVA] [Spiciness Ratings] [2011-12-01 12:12:22] [68da2a3ec537521c4857f5c0bd5ed145]
- RM        [Two-Way ANOVA] [Compendium Week 9] [2011-12-01 12:08:25] [895f9de29a654334f7aa22b48b6b79ac]
- RMPD      [Histogram, QQplot and Density] [] [2011-12-01 12:13:45] [483074838c7eb9e0ff7f7d3e3c3f8586]
- RMPD      [Histogram, QQplot and Density] [Non smokers score...] [2011-12-01 12:15:07] [483074838c7eb9e0ff7f7d3e3c3f8586]
-    D        [Histogram, QQplot and Density] [] [2011-12-01 12:21:02] [483074838c7eb9e0ff7f7d3e3c3f8586]
-    D        [Histogram, QQplot and Density] [] [2011-12-01 12:23:01] [483074838c7eb9e0ff7f7d3e3c3f8586]
-    D        [Histogram, QQplot and Density] [] [2011-12-01 12:33:41] [483074838c7eb9e0ff7f7d3e3c3f8586]
- RMPD        [Aston University Statistical Software] [] [2011-12-01 12:50:30] [483074838c7eb9e0ff7f7d3e3c3f8586]
- R         [Two-Way ANOVA] [] [2011-12-01 12:16:02] [e3bca26b0e60ee0c7c12e4668b30341a]
- R  D      [Two-Way ANOVA] [] [2011-12-01 12:16:50] [84f9d24ffbb976b91a97c3ec996667ce]
- RMPD        [Histogram, QQplot and Density] [] [2011-12-01 12:19:14] [84f9d24ffbb976b91a97c3ec996667ce]
- R PD          [Histogram, QQplot and Density] [Spiciness Ratings...] [2011-12-01 12:40:24] [84f9d24ffbb976b91a97c3ec996667ce]
- R  D          [Histogram, QQplot and Density] [] [2011-12-04 14:48:16] [74be16979710d4c4e7c6647856088456]
- R PD          [Histogram, QQplot and Density] [] [2011-12-04 14:51:41] [74be16979710d4c4e7c6647856088456]
- R PD          [Histogram, QQplot and Density] [] [2011-12-04 14:52:21] [74be16979710d4c4e7c6647856088456]
- R PD          [Histogram, QQplot and Density] [] [2011-12-04 14:53:01] [74be16979710d4c4e7c6647856088456]
- RM        [Two-Way ANOVA] [boxplots week 9] [2011-12-01 12:16:52] [6c7941ad1a28776e0a3d3478d8e8be50]
- RMP       [Histogram, QQplot and Density] [example] [2011-12-01 12:19:02] [57084a6890c0bc671c16163e98194e4e]
- R         [Two-Way ANOVA] [Week 9] [2011-12-01 12:20:42] [4d6fcff7a029721f667cce838c3bc5ec]
- RM        [Two-Way ANOVA] [] [2011-12-01 12:20:43] [6920cf7129d32b5e1d3344311b2c82d4]
- R         [Two-Way ANOVA] [smoker?/curry sta...] [2011-12-01 12:20:56] [bf6019510b5bcef0d7dc6b5e3f13759f]
- RM        [Two-Way ANOVA] [Results for the e...] [2011-12-01 12:17:37] [454fdeac8293fa9258db047c8915ceb3]
- RM        [Two-Way ANOVA] [histogram and box...] [2011-12-01 12:25:24] [04881406e92e7b483917daebdd502463]
- R         [Two-Way ANOVA] [Boxplot for spici...] [2011-12-01 12:26:54] [553711af6a3a99aac240956ee7ba8417]
- RMPD      [Histogram, QQplot and Density] [histogram rating] [2011-12-01 12:27:18] [bee56a896f26c17646228a77f17a2aff]
- RMPD        [Boxplot and Trimmed Means] [box plot smoker n...] [2011-12-01 12:44:04] [bee56a896f26c17646228a77f17a2aff]
- R         [Two-Way ANOVA] [2 way ANOVA for c...] [2011-12-01 12:32:55] [c2d7eae68f5ec0337d2d2ba826377ba0]
- RM        [Two-Way ANOVA] [W9 Two way ANOVA ...] [2011-12-01 12:33:10] [5af04e13c06bbf1f7fb207eb9550d664]
- RM        [Two-Way ANOVA] [comp 9] [2011-12-01 12:33:04] [d2893370a6bab19f4850e41a1f5affd5]
- RM D      [Histogram, QQplot and Density] [smokers rating of...] [2011-12-01 12:34:37] [e3bca26b0e60ee0c7c12e4668b30341a]
- R  D        [Histogram, QQplot and Density] [smokers and korma...] [2011-12-01 12:37:15] [e3bca26b0e60ee0c7c12e4668b30341a]
-    D        [Histogram, QQplot and Density] [non smokers vindaloo] [2011-12-01 12:39:42] [e3bca26b0e60ee0c7c12e4668b30341a]
-    D          [Histogram, QQplot and Density] [non smokers korma] [2011-12-01 12:41:41] [e3bca26b0e60ee0c7c12e4668b30341a]
- R P         [Histogram, QQplot and Density] [Yoddlee] [2012-11-21 10:15:37] [74be16979710d4c4e7c6647856088456]
- RMP       [Histogram, QQplot and Density] [Compendium Week 9 ] [2011-12-01 12:34:40] [895f9de29a654334f7aa22b48b6b79ac]
- RM        [Two-Way ANOVA] [histogrm week 9 ] [2011-12-01 12:36:51] [39ce388efffdeef2308177e33597aa30]
- R         [Two-Way ANOVA] [Checking for homo...] [2011-12-01 12:38:37] [bdeb1591ecf7a4fb2b8ebb6101b513c3]
- R P       [Two-Way ANOVA] [Rating of hotness...] [2011-12-01 12:41:17] [a7ea7f4263337445a0a4c6547fb2278a]
- RMPD      [Notched Boxplots] [Spiciness box plot] [2011-12-01 12:36:29] [8be39d68cf3e859c626e6f1d2306767c]
- RMP       [Histogram, QQplot and Density] [] [2011-12-01 12:44:10] [6920cf7129d32b5e1d3344311b2c82d4]
- RM        [Two-Way ANOVA] [2 way ANOVA] [2011-12-01 12:45:02] [e3bca26b0e60ee0c7c12e4668b30341a]
- RM        [Two-Way ANOVA] [Blog] [2011-12-01 12:48:43] [eaa1051df62e3cae1e5cf7c042ac8911]
- R  D      [Two-Way ANOVA] [curry vs smoker v...] [2011-12-01 12:45:19] [74be16979710d4c4e7c6647856088456]
- R  D      [Two-Way ANOVA] [] [2011-12-01 12:45:19] [74be16979710d4c4e7c6647856088456]
- RM        [Two-Way ANOVA] [] [2011-12-01 12:49:55] [db1d7c04a949ca0eb268b1942f189a57]

[Truncated]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4	'SMK'	'hot'
5	'SMK'	'hot'
3	'SMK'	'hot'
4	'SMK'	'hot'
5	'SMK'	'hot'
3	'SMK'	'hot'
7	'SMK'	'hot'
5	'SMK'	'hot'
6	'SMK'	'hot'
3	'SMK'	'hot'
2	'SMK'	'hot'
4	'SMK'	'hot'
5	'SMK'	'hot'
2	'SMK'	'hot'
3	'SMK'	'hot'
6	'SMK'	'hot'
4	'SMK'	'hot'
4	'SMK'	'hot'
6	'SMK'	'hot'
2	'SMK'	'hot'
3	'SMK'	'mild'
5	'SMK'	'mild'
4	'SMK'	'mild'
2	'SMK'	'mild'
7	'SMK'	'mild'
1	'SMK'	'mild'
4	'SMK'	'mild'
4	'SMK'	'mild'
7	'SMK'	'mild'
4	'SMK'	'mild'
3	'SMK'	'mild'
3	'SMK'	'mild'
3	'SMK'	'mild'
3	'SMK'	'mild'
2	'SMK'	'mild'
5	'SMK'	'mild'
5	'SMK'	'mild'
3	'SMK'	'mild'
6	'SMK'	'mild'
2	'SMK'	'mild'
8	'NS'	'hot'
9	'NS'	'hot'
10	'NS'	'hot'
7	'NS'	'hot'
8	'NS'	'hot'
9	'NS'	'hot'
10	'NS'	'hot'
6	'NS'	'hot'
6	'NS'	'hot'
7	'NS'	'hot'
8	'NS'	'hot'
9	'NS'	'hot'
8	'NS'	'hot'
7	'NS'	'hot'
5	'NS'	'hot'
11	'NS'	'hot'
7	'NS'	'hot'
8	'NS'	'hot'
10	'NS'	'hot'
9	'NS'	'hot'
3	'NS'	'mild'
5	'NS'	'mild'
4	'NS'	'mild'
2	'NS'	'mild'
6	'NS'	'mild'
1	'NS'	'mild'
4	'NS'	'mild'
4	'NS'	'mild'
5	'NS'	'mild'
4	'NS'	'mild'
3	'NS'	'mild'
3	'NS'	'mild'
4	'NS'	'mild'
3	'NS'	'mild'
2	'NS'	'mild'
5	'NS'	'mild'
4	'NS'	'mild'
3	'NS'	'mild'
6	'NS'	'mild'
2	'NS'	'mild'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147905&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147905&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147905&T=0

As an alternative you can also use a QR Code:  
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'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
Response ~ Treatment_A * Treatment_B
means8.1-3.95-4.454.1

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 8.1 & -3.95 & -4.45 & 4.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147905&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]8.1[/C][C]-3.95[/C][C]-4.45[/C][C]4.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147905&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147905&T=1

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Model
Response ~ Treatment_A * Treatment_B
means8.1-3.95-4.454.1






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A172.272.231.8840
Treatment_B1115.2115.250.8730
Treatment_A:Treatment_B184.0584.0537.1170
Residuals76172.12.264 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 72.2 & 72.2 & 31.884 & 0 \tabularnewline
Treatment_B & 1 & 115.2 & 115.2 & 50.873 & 0 \tabularnewline
Treatment_A:Treatment_B & 1 & 84.05 & 84.05 & 37.117 & 0 \tabularnewline
Residuals & 76 & 172.1 & 2.264 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147905&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]Treatment_A[/C][C]1[/C][C]72.2[/C][C]72.2[/C][C]31.884[/C][C]0[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]115.2[/C][C]115.2[/C][C]50.873[/C][C]0[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]84.05[/C][C]84.05[/C][C]37.117[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]76[/C][C]172.1[/C][C]2.264[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147905&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147905&T=2

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A172.272.231.8840
Treatment_B1115.2115.250.8730
Treatment_A:Treatment_B184.0584.0537.1170
Residuals76172.12.264






Tukey Honest Significant Difference Comparisons
difflwruprp adj
SMK-NS-1.9-2.57-1.230
mild-hot-2.4-3.07-1.730
SMK:hot-NS:hot-3.95-5.2-2.70
NS:mild-NS:hot-4.45-5.7-3.20
SMK:mild-NS:hot-4.3-5.55-3.050
NS:mild-SMK:hot-0.5-1.750.750.72
SMK:mild-SMK:hot-0.35-1.60.90.882
SMK:mild-NS:mild0.15-1.11.40.989

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
SMK-NS & -1.9 & -2.57 & -1.23 & 0 \tabularnewline
mild-hot & -2.4 & -3.07 & -1.73 & 0 \tabularnewline
SMK:hot-NS:hot & -3.95 & -5.2 & -2.7 & 0 \tabularnewline
NS:mild-NS:hot & -4.45 & -5.7 & -3.2 & 0 \tabularnewline
SMK:mild-NS:hot & -4.3 & -5.55 & -3.05 & 0 \tabularnewline
NS:mild-SMK:hot & -0.5 & -1.75 & 0.75 & 0.72 \tabularnewline
SMK:mild-SMK:hot & -0.35 & -1.6 & 0.9 & 0.882 \tabularnewline
SMK:mild-NS:mild & 0.15 & -1.1 & 1.4 & 0.989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147905&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]SMK-NS[/C][C]-1.9[/C][C]-2.57[/C][C]-1.23[/C][C]0[/C][/ROW]
[ROW][C]mild-hot[/C][C]-2.4[/C][C]-3.07[/C][C]-1.73[/C][C]0[/C][/ROW]
[ROW][C]SMK:hot-NS:hot[/C][C]-3.95[/C][C]-5.2[/C][C]-2.7[/C][C]0[/C][/ROW]
[ROW][C]NS:mild-NS:hot[/C][C]-4.45[/C][C]-5.7[/C][C]-3.2[/C][C]0[/C][/ROW]
[ROW][C]SMK:mild-NS:hot[/C][C]-4.3[/C][C]-5.55[/C][C]-3.05[/C][C]0[/C][/ROW]
[ROW][C]NS:mild-SMK:hot[/C][C]-0.5[/C][C]-1.75[/C][C]0.75[/C][C]0.72[/C][/ROW]
[ROW][C]SMK:mild-SMK:hot[/C][C]-0.35[/C][C]-1.6[/C][C]0.9[/C][C]0.882[/C][/ROW]
[ROW][C]SMK:mild-NS:mild[/C][C]0.15[/C][C]-1.1[/C][C]1.4[/C][C]0.989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147905&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147905&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
SMK-NS-1.9-2.57-1.230
mild-hot-2.4-3.07-1.730
SMK:hot-NS:hot-3.95-5.2-2.70
NS:mild-NS:hot-4.45-5.7-3.20
SMK:mild-NS:hot-4.3-5.55-3.050
NS:mild-SMK:hot-0.5-1.750.750.72
SMK:mild-SMK:hot-0.35-1.60.90.882
SMK:mild-NS:mild0.15-1.11.40.989






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.250.861
76 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.25 & 0.861 \tabularnewline
  & 76 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147905&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]3[/C][C]0.25[/C][C]0.861[/C][/ROW]
[ROW][C] [/C][C]76[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147905&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147905&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.250.861
76


Figures (Output of Computation)

Input Parameters & R Code

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')