Free Statistics

of Irreproducible Research!

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, 27 Nov 2012 04:02:12 -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/2012/Nov/27/t1354007043cjxwr6w4lbf0gm2.htm/, Retrieved Sat, 04 May 2024 14:50:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=193790, Retrieved Sat, 04 May 2024 14:50:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact254
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Two-Way ANOVA] [] [2012-11-27 09:02:12] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
Feedback Forum

Post a new message
Dataseries X:
102	'UK'	'HI'
99	'UK'	'LO'
97	'UK'	'LO'
82	'UK'	'HI'
77	'UK'	'HI'
65	'UK'	'LO'
64	'UK'	'LO'
62	'UK'	'LO'
62	'UK'	'LO'
62	'UK'	'HI'
61	'UK'	'LO'
59	'UK'	'LO'
57	'UK'	'LO'
56	'UK'	'HI'
54	'UK'	'LO'
54	'UK'	'LO'
53	'UK'	'LO'
52	'UK'	'HI'
51	'UK'	'LO'
51	'UK'	'LO'
51	'UK'	'HI'
50	'UK'	'HI'
50	'UK'	'LO'
50	'UK'	'LO'
49	'UK'	'LO'
49	'UK'	'HI'
49	'UK'	'LO'
48	'UK'	'LO'
48	'UK'	'LO'
47	'UK'	'LO'
47	'UK'	'LO'
46	'UK'	'LO'
46	'UK'	'LO'
45	'UK'	'HI'
45	'UK'	'LO'
45	'UK'	'LO'
44	'UK'	'LO'
43	'UK'	'LO'
42	'UK'	'HI'
42	'UK'	'LO'
42	'UK'	'LO'
42	'UK'	'LO'
42	'UK'	'HI'
42	'UK'	'LO'
41	'UK'	'HI'
41	'UK'	'LO'
41	'UK'	'LO'
41	'UK'	'HI'
41	'UK'	'HI'
41	'UK'	'HI'
41	'UK'	'HI'
40	'UK'	'LO'
40	'UK'	'LO'
40	'UK'	'HI'
40	'UK'	'HI'
40	'UK'	'LO'
39	'UK'	'HI'
39	'UK'	'LO'
38	'UK'	'LO'
38	'UK'	'HI'
36	'UK'	'LO'
36	'UK'	'LO'
35	'UK'	'LO'
35	'UK'	'HI'
35	'UK'	'HI'
35	'UK'	'LO'
34	'UK'	'LO'
34	'UK'	'LO'
34	'UK'	'LO'
33	'UK'	'LO'
33	'UK'	'HI'
33	'UK'	'LO'
32	'UK'	'LO'
32	'UK'	'LO'
32	'UK'	'LO'
31	'UK'	'HI'
31	'UK'	'LO'
30	'UK'	'LO'
30	'UK'	'HI'
30	'UK'	'LO'
30	'UK'	'LO'
29	'UK'	'LO'
28	'UK'	'HI'
28	'UK'	'HI'
27	'UK'	'LO'
27	'UK'	'LO'
27	'UK'	'LO'
26	'UK'	'LO'
25	'UK'	'LO'
25	'UK'	'HI'
25	'UK'	'LO'
24	'UK'	'LO'
24	'UK'	'LO'
23	'UK'	'LO'
23	'UK'	'HI'
23	'UK'	'LO'
23	'UK'	'HI'
23	'UK'	'HI'
22	'UK'	'LO'
22	'UK'	'LO'
22	'UK'	'LO'
22	'UK'	'HI'
20	'UK'	'HI'
19	'UK'	'LO'
19	'UK'	'LO'
17	'UK'	'HI'
17	'UK'	'LO'
16	'UK'	'HI'
16	'UK'	'HI'
5	'UK'	'LO'
4	'UK'	'LO'
3	'UK'	'HI'
3	'UK'	'LO'
1	'UK'	'HI'
156	'B'	'LO'
109	'B'	'HI'
104	'B'	'LO'
98	'B'	'LO'
78	'B'	'LO'
77	'B'	'LO'
73	'B'	'LO'
71	'B'	'LO'
67	'B'	'LO'
64	'B'	'HI'
62	'B'	'LO'
61	'B'	'LO'
58	'B'	'LO'
58	'B'	'HI'
56	'B'	'LO'
56	'B'	'LO'
52	'B'	'LO'
51	'B'	'LO'
51	'B'	'LO'
50	'B'	'LO'
49	'B'	'HI'
49	'B'	'LO'
48	'B'	'LO'
47	'B'	'LO'
47	'B'	'LO'
46	'B'	'LO'
45	'B'	'HI'
45	'B'	'LO'
45	'B'	'HI'
45	'B'	'HI'
44	'B'	'LO'
44	'B'	'LO'
44	'B'	'LO'
43	'B'	'LO'
43	'B'	'LO'
42	'B'	'HI'
41	'B'	'LO'
41	'B'	'HI'
40	'B'	'LO'
39	'B'	'LO'
39	'B'	'LO'
39	'B'	'LO'
39	'B'	'LO'
39	'B'	'LO'
39	'B'	'LO'
39	'B'	'HI'
38	'B'	'LO'
38	'B'	'LO'
38	'B'	'HI'
38	'B'	'HI'
37	'B'	'HI'
37	'B'	'HI'
37	'B'	'HI'
36	'B'	'LO'
36	'B'	'HI'
36	'B'	'LO'
36	'B'	'HI'
36	'B'	'LO'
36	'B'	'LO'
35	'B'	'LO'
35	'B'	'LO'
34	'B'	'HI'
34	'B'	'LO'
34	'B'	'HI'
34	'B'	'LO'
34	'B'	'LO'
33	'B'	'LO'
33	'B'	'HI'
33	'B'	'LO'
33	'B'	'LO'
33	'B'	'HI'
33	'B'	'LO'
32	'B'	'HI'
32	'B'	'HI'
32	'B'	'HI'
32	'B'	'HI'
32	'B'	'HI'
31	'B'	'LO'
31	'B'	'LO'
31	'B'	'HI'
30	'B'	'HI'
30	'B'	'HI'
29	'B'	'LO'
29	'B'	'HI'
29	'B'	'HI'
28	'B'	'LO'
28	'B'	'HI'
28	'B'	'HI'
28	'B'	'LO'
28	'B'	'LO'
28	'B'	'HI'
27	'B'	'LO'
27	'B'	'HI'
27	'B'	'LO'
26	'B'	'LO'
26	'B'	'HI'
26	'B'	'LO'
26	'B'	'LO'
25	'B'	'LO'
25	'B'	'HI'
24	'B'	'HI'
24	'B'	'LO'
24	'B'	'HI'
24	'B'	'LO'
24	'B'	'LO'
24	'B'	'HI'
24	'B'	'LO'
23	'B'	'HI'
23	'B'	'HI'
23	'B'	'LO'
23	'B'	'HI'
23	'B'	'LO'
23	'B'	'LO'
23	'B'	'LO'
22	'B'	'LO'
22	'B'	'HI'
21	'B'	'HI'
21	'B'	'LO'
21	'B'	'LO'
21	'B'	'LO'
20	'B'	'HI'
20	'B'	'HI'
20	'B'	'LO'
20	'B'	'HI'
20	'B'	'HI'
19	'B'	'HI'
19	'B'	'HI'
19	'B'	'HI'
18	'B'	'HI'
18	'B'	'LO'
18	'B'	'LO'
18	'B'	'HI'
18	'B'	'LO'
17	'B'	'HI'
17	'B'	'HI'
17	'B'	'HI'
16	'B'	'HI'
16	'B'	'LO'
15	'B'	'HI'
15	'B'	'HI'
15	'B'	'HI'
15	'B'	'HI'
14	'B'	'HI'
13	'B'	'HI'
13	'B'	'LO'
12	'B'	'LO'
11	'B'	'HI'
11	'B'	'LO'
10	'B'	'HI'
10	'B'	'HI'
10	'B'	'LO'
10	'B'	'LO'
9	'B'	'HI'
8	'B'	'HI'
8	'B'	'HI'
8	'B'	'HI'
7	'B'	'HI'
7	'B'	'HI'
6	'B'	'HI'
4	'B'	'HI'
4	'B'	'HI'
2	'B'	'HI'
1	'B'	'HI'
1	'B'	'HI'
1	'B'	'HI'
0	'B'	'HI'
0	'B'	'HI'
0	'B'	'HI'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 4 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193790&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193790&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 time4 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







ANOVA Model
Response ~ Treatment_A * Treatment_B
means24.20513.7714.748-13.616

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response ~ Treatment_A * Treatment_B \tabularnewline
means & 24.205 & 13.77 & 14.748 & -13.616 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193790&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response ~ Treatment_A * Treatment_B[/C][/ROW]
[ROW][C]means[/C][C]24.205[/C][C]13.77[/C][C]14.748[/C][C]-13.616[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193790&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
means24.20513.7714.748-13.616







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
1
Treatment_A13378.063378.069.3540.002
Treatment_B16214.2256214.22517.2080
Treatment_A:Treatment_B12952.6752952.6758.1760.005
Residuals278100393.451361.128

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
 & 1 &  &  &  &  \tabularnewline
Treatment_A & 1 & 3378.06 & 3378.06 & 9.354 & 0.002 \tabularnewline
Treatment_B & 1 & 6214.225 & 6214.225 & 17.208 & 0 \tabularnewline
Treatment_A:Treatment_B & 1 & 2952.675 & 2952.675 & 8.176 & 0.005 \tabularnewline
Residuals & 278 & 100393.451 & 361.128 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193790&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]3378.06[/C][C]3378.06[/C][C]9.354[/C][C]0.002[/C][/ROW]
[ROW][C]Treatment_B[/C][C]1[/C][C]6214.225[/C][C]6214.225[/C][C]17.208[/C][C]0[/C][/ROW]
[ROW][C]Treatment_A:Treatment_B[/C][C]1[/C][C]2952.675[/C][C]2952.675[/C][C]8.176[/C][C]0.005[/C][/ROW]
[ROW][C]Residuals[/C][C]278[/C][C]100393.451[/C][C]361.128[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193790&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193790&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
Treatment_A13378.063378.069.3540.002
Treatment_B16214.2256214.22517.2080
Treatment_A:Treatment_B12952.6752952.6758.1760.005
Residuals278100393.451361.128







Tukey Honest Significant Difference Comparisons
difflwruprp adj
UK-B7.0532.51311.5920.002
LO-HI9.3674.87113.8630
UK:HI-B:HI13.774.23423.3050.001
B:LO-B:HI14.7487.16922.3280
UK:LO-B:HI14.9027.07722.7270
B:LO-UK:HI0.979-8.52110.4780.993
UK:LO-UK:HI1.132-8.56410.8290.99
UK:LO-B:LO0.154-7.6287.9351

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
UK-B & 7.053 & 2.513 & 11.592 & 0.002 \tabularnewline
LO-HI & 9.367 & 4.871 & 13.863 & 0 \tabularnewline
UK:HI-B:HI & 13.77 & 4.234 & 23.305 & 0.001 \tabularnewline
B:LO-B:HI & 14.748 & 7.169 & 22.328 & 0 \tabularnewline
UK:LO-B:HI & 14.902 & 7.077 & 22.727 & 0 \tabularnewline
B:LO-UK:HI & 0.979 & -8.521 & 10.478 & 0.993 \tabularnewline
UK:LO-UK:HI & 1.132 & -8.564 & 10.829 & 0.99 \tabularnewline
UK:LO-B:LO & 0.154 & -7.628 & 7.935 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193790&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]UK-B[/C][C]7.053[/C][C]2.513[/C][C]11.592[/C][C]0.002[/C][/ROW]
[ROW][C]LO-HI[/C][C]9.367[/C][C]4.871[/C][C]13.863[/C][C]0[/C][/ROW]
[ROW][C]UK:HI-B:HI[/C][C]13.77[/C][C]4.234[/C][C]23.305[/C][C]0.001[/C][/ROW]
[ROW][C]B:LO-B:HI[/C][C]14.748[/C][C]7.169[/C][C]22.328[/C][C]0[/C][/ROW]
[ROW][C]UK:LO-B:HI[/C][C]14.902[/C][C]7.077[/C][C]22.727[/C][C]0[/C][/ROW]
[ROW][C]B:LO-UK:HI[/C][C]0.979[/C][C]-8.521[/C][C]10.478[/C][C]0.993[/C][/ROW]
[ROW][C]UK:LO-UK:HI[/C][C]1.132[/C][C]-8.564[/C][C]10.829[/C][C]0.99[/C][/ROW]
[ROW][C]UK:LO-B:LO[/C][C]0.154[/C][C]-7.628[/C][C]7.935[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193790&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193790&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
UK-B7.0532.51311.5920.002
LO-HI9.3674.87113.8630
UK:HI-B:HI13.774.23423.3050.001
B:LO-B:HI14.7487.16922.3280
UK:LO-B:HI14.9027.07722.7270
B:LO-UK:HI0.979-8.52110.4780.993
UK:LO-UK:HI1.132-8.56410.8290.99
UK:LO-B:LO0.154-7.6287.9351







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.5560.644
278

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.556 & 0.644 \tabularnewline
  & 278 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193790&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]0.556[/C][C]0.644[/C][/ROW]
[ROW][C] [/C][C]278[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193790&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193790&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)
Group30.5560.644
278



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 <- 'TRUE'
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')