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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, 04 Nov 2013 14:18:46 -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/2013/Nov/04/t1383592739pcas1rd32hub94d.htm/, Retrieved Sat, 27 Apr 2024 16:11:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=222187, Retrieved Sat, 27 Apr 2024 16:11:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-04 18:35:53] [50191575d7f9c958084e7e760a37a7f0]
- RMP   [Paired and Unpaired Two Samples Tests about the Mean] [] [2013-11-04 19:03:02] [50191575d7f9c958084e7e760a37a7f0]
- RMPD      [Two-Way ANOVA] [] [2013-11-04 19:18:46] [0968a8b67fc621ded3325342a6e4b095] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 0 'E'
0 1 'F'
1 0 'F'
1 0 'H'
1 0 'H'
1 0 'H'
1 1 'E'
1 1 'F'
1 0 'E'
0 1 'F'
0 0 'H'
0 0 'E'
1 1 'F'
0 0 'H'
0 1 'E'
0 0 'H'
1 0 'E'
1 0 'F'
0 0 'H'
0 1 'F'
0 0 'H'
1 0 'H'
0 0 'H'
0 0 'E'
0 1 'F'
0 1 'E'
0 1 'E'
1 0 'F'
0 0 'F'
0 0 'H'
1 0 'E'
1 1 'E'
1 0 'H'
1 1 'E'
1 1 'F'
1 0 'E'
0 1 'F'
0 0 'H'
0 1 'E'
0 1 'F'
0 1 'F'
0 0 'F'
0 1 'F'
1 1 'H'
0 1 'E'
0 0 'E'
0 0 'H'
1 1 'E'
1 0 'F'
0 0 'F'
0 0 'H'
1 0 'E'
1 1 'F'
1 1 'E'
1 0 'H'
1 0 'H'
1 0 'H'
1 0 'E'
0 0 'H'
0 1 'E'
1 0 'H'
1 0 'F'
1 0 'H'
0 1 'F'
1 0 'E'
1 1 'E'
0 0 'F'
1 0 'H'
0 0 'F'
1 0 'E'
1 -1 'E'
0 0 'H'
1 0 'H'
1 0 'F'
1 0 'H'
0 1 'E'
1 0 'F'
0 1 'E'
0 0 'E'
0 0 'E'
1 0 'F'
1 0 'E'
1 1 'F'
1 0 'H'
1 0 'H'
1 0 'H'
0 0 'F'
1 0 'H'
1 0 'H'
1 1 'F'
1 1 'F'
0 0 'H'
1 0 'F'
1 0 'H'
0 0 'E'
1 1 'F'
0 0 'E'
1 0 'H'
1 1 'F'
1 0 'F'
1 0 'H'
1 1 'E'
0 0 'F'
1 0 'H'
1 0 'E'
0 0 'F'
0 0 'H'
1 0 'H'
1 1 'F'
1 1 'F'
1 0 'H'
0 0 'E'
1 0 'H'
1 0 'E'
0 0 'E'
1 0 'F'
1 0 'F'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222187&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]6 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=222187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222187&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 time6 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
Response ~ Treatment_A * Treatment_B
means1-0.429-0.5330.0830.533-0.055NA-0.464NA

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 1 & -0.429 & -0.533 & 0.083 & 0.533 & -0.055 & NA & -0.464 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222187&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]1[/C][C]-0.429[/C][C]-0.533[/C][C]0.083[/C][C]0.533[/C][C]-0.055[/C][C]NA[/C][C]-0.464[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222187&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
means1-0.429-0.5330.0830.533-0.055NA-0.464NA






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
2
Treatment_A20.3480.1740.6930.502
Treatment_B20.170.0850.3390.713
Treatment_A:Treatment_B20.1890.0940.3770.687
Residuals11027.6010.251 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 2 &  &  &  &  \tabularnewline
Treatment_A & 2 & 0.348 & 0.174 & 0.693 & 0.502 \tabularnewline
Treatment_B & 2 & 0.17 & 0.085 & 0.339 & 0.713 \tabularnewline
Treatment_A:Treatment_B & 2 & 0.189 & 0.094 & 0.377 & 0.687 \tabularnewline
Residuals & 110 & 27.601 & 0.251 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222187&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]0.348[/C][C]0.174[/C][C]0.693[/C][C]0.502[/C][/ROW]
[ROW][C]Treatment_B[/C][C]2[/C][C]0.17[/C][C]0.085[/C][C]0.339[/C][C]0.713[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]2[/C][C]0.189[/C][C]0.094[/C][C]0.377[/C][C]0.687[/C][/ROW]
[ROW][C]Residuals[/C][C]110[/C][C]27.601[/C][C]0.251[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222187&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222187&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)
2
Treatment_A20.3480.1740.6930.502
Treatment_B20.170.0850.3390.713
Treatment_A:Treatment_B20.1890.0940.3770.687
Residuals11027.6010.251






Tukey Honest Significant Difference Comparisons
difflwruprp adj
0--1-0.387-1.5850.810.723
1--1-0.472-1.6790.7340.623
1-0-0.085-0.3240.1540.677
F-E0.053-0.2190.3240.889
H-E0.088-0.1840.3590.724
H-F0.035-0.2310.3010.948
0:E--1:E-0.429-2.0511.1940.995
1:E--1:E-0.533-2.171.1040.982
-1:F--1:ENANANANA
0:F--1:E-0.4-2.0241.2240.997
1:F--1:E-0.45-2.0741.1740.994
-1:H--1:ENANANANA
0:H--1:E-0.359-1.9641.2460.999
1:H--1:E0-2.2422.2421
1:E-0:E-0.105-0.6410.4310.999
-1:F-0:ENANANANA
0:F-0:E0.029-0.4670.5241
1:F-0:E-0.021-0.5170.4741
-1:H-0:ENANANANA
0:H-0:E0.07-0.3590.4991
1:H-0:E0.429-1.1942.0510.995
-1:F-1:ENANANANA
0:F-1:E0.133-0.4080.6750.997
1:F-1:E0.083-0.4580.6251
-1:H-1:ENANANANA
0:H-1:E0.174-0.3070.6560.966
1:H-1:E0.533-1.1042.170.982
0:F--1:FNANANANA
1:F--1:FNANANANA
-1:H--1:FNANANANA
0:H--1:FNANANANA
1:H--1:FNANANANA
1:F-0:F-0.05-0.5510.4511
-1:H-0:FNANANANA
0:H-0:F0.041-0.3950.4771
1:H-0:F0.4-1.2242.0240.997
-1:H-1:FNANANANA
0:H-1:F0.091-0.3450.5270.999
1:H-1:F0.45-1.1742.0740.994
0:H--1:HNANANANA
1:H--1:HNANANANA
1:H-0:H0.359-1.2461.9640.999

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
0--1 & -0.387 & -1.585 & 0.81 & 0.723 \tabularnewline
1--1 & -0.472 & -1.679 & 0.734 & 0.623 \tabularnewline
1-0 & -0.085 & -0.324 & 0.154 & 0.677 \tabularnewline
F-E & 0.053 & -0.219 & 0.324 & 0.889 \tabularnewline
H-E & 0.088 & -0.184 & 0.359 & 0.724 \tabularnewline
H-F & 0.035 & -0.231 & 0.301 & 0.948 \tabularnewline
0:E--1:E & -0.429 & -2.051 & 1.194 & 0.995 \tabularnewline
1:E--1:E & -0.533 & -2.17 & 1.104 & 0.982 \tabularnewline
-1:F--1:E & NA & NA & NA & NA \tabularnewline
0:F--1:E & -0.4 & -2.024 & 1.224 & 0.997 \tabularnewline
1:F--1:E & -0.45 & -2.074 & 1.174 & 0.994 \tabularnewline
-1:H--1:E & NA & NA & NA & NA \tabularnewline
0:H--1:E & -0.359 & -1.964 & 1.246 & 0.999 \tabularnewline
1:H--1:E & 0 & -2.242 & 2.242 & 1 \tabularnewline
1:E-0:E & -0.105 & -0.641 & 0.431 & 0.999 \tabularnewline
-1:F-0:E & NA & NA & NA & NA \tabularnewline
0:F-0:E & 0.029 & -0.467 & 0.524 & 1 \tabularnewline
1:F-0:E & -0.021 & -0.517 & 0.474 & 1 \tabularnewline
-1:H-0:E & NA & NA & NA & NA \tabularnewline
0:H-0:E & 0.07 & -0.359 & 0.499 & 1 \tabularnewline
1:H-0:E & 0.429 & -1.194 & 2.051 & 0.995 \tabularnewline
-1:F-1:E & NA & NA & NA & NA \tabularnewline
0:F-1:E & 0.133 & -0.408 & 0.675 & 0.997 \tabularnewline
1:F-1:E & 0.083 & -0.458 & 0.625 & 1 \tabularnewline
-1:H-1:E & NA & NA & NA & NA \tabularnewline
0:H-1:E & 0.174 & -0.307 & 0.656 & 0.966 \tabularnewline
1:H-1:E & 0.533 & -1.104 & 2.17 & 0.982 \tabularnewline
0:F--1:F & NA & NA & NA & NA \tabularnewline
1:F--1:F & NA & NA & NA & NA \tabularnewline
-1:H--1:F & NA & NA & NA & NA \tabularnewline
0:H--1:F & NA & NA & NA & NA \tabularnewline
1:H--1:F & NA & NA & NA & NA \tabularnewline
1:F-0:F & -0.05 & -0.551 & 0.451 & 1 \tabularnewline
-1:H-0:F & NA & NA & NA & NA \tabularnewline
0:H-0:F & 0.041 & -0.395 & 0.477 & 1 \tabularnewline
1:H-0:F & 0.4 & -1.224 & 2.024 & 0.997 \tabularnewline
-1:H-1:F & NA & NA & NA & NA \tabularnewline
0:H-1:F & 0.091 & -0.345 & 0.527 & 0.999 \tabularnewline
1:H-1:F & 0.45 & -1.174 & 2.074 & 0.994 \tabularnewline
0:H--1:H & NA & NA & NA & NA \tabularnewline
1:H--1:H & NA & NA & NA & NA \tabularnewline
1:H-0:H & 0.359 & -1.246 & 1.964 & 0.999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222187&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]0--1[/C][C]-0.387[/C][C]-1.585[/C][C]0.81[/C][C]0.723[/C][/ROW]
[ROW][C]1--1[/C][C]-0.472[/C][C]-1.679[/C][C]0.734[/C][C]0.623[/C][/ROW]
[ROW][C]1-0[/C][C]-0.085[/C][C]-0.324[/C][C]0.154[/C][C]0.677[/C][/ROW]
[ROW][C]F-E[/C][C]0.053[/C][C]-0.219[/C][C]0.324[/C][C]0.889[/C][/ROW]
[ROW][C]H-E[/C][C]0.088[/C][C]-0.184[/C][C]0.359[/C][C]0.724[/C][/ROW]
[ROW][C]H-F[/C][C]0.035[/C][C]-0.231[/C][C]0.301[/C][C]0.948[/C][/ROW]
[ROW][C]0:E--1:E[/C][C]-0.429[/C][C]-2.051[/C][C]1.194[/C][C]0.995[/C][/ROW]
[ROW][C]1:E--1:E[/C][C]-0.533[/C][C]-2.17[/C][C]1.104[/C][C]0.982[/C][/ROW]
[ROW][C]-1:F--1:E[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:F--1:E[/C][C]-0.4[/C][C]-2.024[/C][C]1.224[/C][C]0.997[/C][/ROW]
[ROW][C]1:F--1:E[/C][C]-0.45[/C][C]-2.074[/C][C]1.174[/C][C]0.994[/C][/ROW]
[ROW][C]-1:H--1:E[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:H--1:E[/C][C]-0.359[/C][C]-1.964[/C][C]1.246[/C][C]0.999[/C][/ROW]
[ROW][C]1:H--1:E[/C][C]0[/C][C]-2.242[/C][C]2.242[/C][C]1[/C][/ROW]
[ROW][C]1:E-0:E[/C][C]-0.105[/C][C]-0.641[/C][C]0.431[/C][C]0.999[/C][/ROW]
[ROW][C]-1:F-0:E[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:F-0:E[/C][C]0.029[/C][C]-0.467[/C][C]0.524[/C][C]1[/C][/ROW]
[ROW][C]1:F-0:E[/C][C]-0.021[/C][C]-0.517[/C][C]0.474[/C][C]1[/C][/ROW]
[ROW][C]-1:H-0:E[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:H-0:E[/C][C]0.07[/C][C]-0.359[/C][C]0.499[/C][C]1[/C][/ROW]
[ROW][C]1:H-0:E[/C][C]0.429[/C][C]-1.194[/C][C]2.051[/C][C]0.995[/C][/ROW]
[ROW][C]-1:F-1:E[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:F-1:E[/C][C]0.133[/C][C]-0.408[/C][C]0.675[/C][C]0.997[/C][/ROW]
[ROW][C]1:F-1:E[/C][C]0.083[/C][C]-0.458[/C][C]0.625[/C][C]1[/C][/ROW]
[ROW][C]-1:H-1:E[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:H-1:E[/C][C]0.174[/C][C]-0.307[/C][C]0.656[/C][C]0.966[/C][/ROW]
[ROW][C]1:H-1:E[/C][C]0.533[/C][C]-1.104[/C][C]2.17[/C][C]0.982[/C][/ROW]
[ROW][C]0:F--1:F[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]1:F--1:F[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]-1:H--1:F[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:H--1:F[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]1:H--1:F[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]1:F-0:F[/C][C]-0.05[/C][C]-0.551[/C][C]0.451[/C][C]1[/C][/ROW]
[ROW][C]-1:H-0:F[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:H-0:F[/C][C]0.041[/C][C]-0.395[/C][C]0.477[/C][C]1[/C][/ROW]
[ROW][C]1:H-0:F[/C][C]0.4[/C][C]-1.224[/C][C]2.024[/C][C]0.997[/C][/ROW]
[ROW][C]-1:H-1:F[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]0:H-1:F[/C][C]0.091[/C][C]-0.345[/C][C]0.527[/C][C]0.999[/C][/ROW]
[ROW][C]1:H-1:F[/C][C]0.45[/C][C]-1.174[/C][C]2.074[/C][C]0.994[/C][/ROW]
[ROW][C]0:H--1:H[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]1:H--1:H[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]1:H-0:H[/C][C]0.359[/C][C]-1.246[/C][C]1.964[/C][C]0.999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222187&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222187&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
0--1-0.387-1.5850.810.723
1--1-0.472-1.6790.7340.623
1-0-0.085-0.3240.1540.677
F-E0.053-0.2190.3240.889
H-E0.088-0.1840.3590.724
H-F0.035-0.2310.3010.948
0:E--1:E-0.429-2.0511.1940.995
1:E--1:E-0.533-2.171.1040.982
-1:F--1:ENANANANA
0:F--1:E-0.4-2.0241.2240.997
1:F--1:E-0.45-2.0741.1740.994
-1:H--1:ENANANANA
0:H--1:E-0.359-1.9641.2460.999
1:H--1:E0-2.2422.2421
1:E-0:E-0.105-0.6410.4310.999
-1:F-0:ENANANANA
0:F-0:E0.029-0.4670.5241
1:F-0:E-0.021-0.5170.4741
-1:H-0:ENANANANA
0:H-0:E0.07-0.3590.4991
1:H-0:E0.429-1.1942.0510.995
-1:F-1:ENANANANA
0:F-1:E0.133-0.4080.6750.997
1:F-1:E0.083-0.4580.6251
-1:H-1:ENANANANA
0:H-1:E0.174-0.3070.6560.966
1:H-1:E0.533-1.1042.170.982
0:F--1:FNANANANA
1:F--1:FNANANANA
-1:H--1:FNANANANA
0:H--1:FNANANANA
1:H--1:FNANANANA
1:F-0:F-0.05-0.5510.4511
-1:H-0:FNANANANA
0:H-0:F0.041-0.3950.4771
1:H-0:F0.4-1.2242.0240.997
-1:H-1:FNANANANA
0:H-1:F0.091-0.3450.5270.999
1:H-1:F0.45-1.1742.0740.994
0:H--1:HNANANANA
1:H--1:HNANANANA
1:H-0:H0.359-1.2461.9640.999






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group60.3450.912
110 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 6 & 0.345 & 0.912 \tabularnewline
  & 110 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=222187&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]6[/C][C]0.345[/C][C]0.912[/C][/ROW]
[ROW][C] [/C][C]110[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=222187&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=222187&T=4

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group60.3450.912
110


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')