Dear All user,
Hello,
I'm a student and I have some trouble with the experimental
(columns-experiments) design of my project. I use a randomized block design
with 4 treatments including a control. For each treatment, I use 3
replicates and 3 blocks.
The treatments are:
-T1 = COD (300 mg/Lit) COD=chemical oxygen demand
-T2 = COD (200 mg/Lit)
-T3 = COD (100 mg/Lit)
-T4 = COD (0 mg/Lit) as a control
The experiment is conducted during three months and a sample is taken each
Week in every experimental unit.
At the first, I irrigated all soil columns (12 columns) with demonize water
for 1 week.
Then during 8 weeks, I irrigated all columns with waste water with different
concentration. Then, gain, I irrigated all columns with demonize water for 4
weeks.
Now I want to know how I can analyses the results in R. For example, I want
to detect the
Effect of waste water on some physical properties of soil, before, during
use waste water and after use waste water (Is there any significant change
in properties of soil.) Time is also important, so I want to know the
interaction between time and some physical properties of soil, like water
content .first comprises between Treatments and then comprise between
weeks).
Questions to be answered:
1) Theta (water content), before (1 week) and after the COD; is there a
difference?
2) Theta, during, before and after the COD; is there a difference?
3) Is there a trend in Theta, during COD (8 weeks)?
4) Is there a difference in Theta, during COD between the treatments?
I hope somebody can help me to find correct statistical analyses in R. I
sepnt a lot of time, but still , i have problems.
Kind regards,
Alisia
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Week Date BTC timeexp column Block Treatment Condition
ThetaV
0 22/jun/08 -4 1 1 T4 DW 0,0962
Irrigation with diminirize water
0 22/jun/08 -4 2 1 T4 DW 0,0935
Irrigation with diminirize water
0 22/jun/08 -4 3 1 T4 DW 0,1181
Irrigation with diminirize water
0 22/jun/08 -4 4 1 T4 DW 0,0752
Irrigation with diminirize water
0 22/jun/08 -4 5 2 T4 DW 0,0761
Irrigation with diminirize water
0 22/jun/08 -4 6 2 T4 DW 0,0729
Irrigation with diminirize water
0 25/jun/08 -1 7 2 T4 DW 0,076
Irrigation with diminirize water
0 25/jun/08 -1 8 2 T4 DW 0,0766
Irrigation with diminirize water
0 25/jun/08 -1 9 3 T4 DW 0,0981
Irrigation with diminirize water
0 25/jun/08 -1 10 3 T4 DW 0,0628
Irrigation with diminirize water
0 25/jun/08 -1 11 3 T4 DW 0,0867
Irrigation with diminirize water
0 25/jun/08 -1 12 3 T4 DW 0,0657
Irrigation with diminirize water
1 27/jun/08 1 1 1 T3 WW 0,0903
Irrigation with wastewater
1 27/jun/08 1 2 1 T2 WW 0,0864
Irrigation with wastewater
1 27/jun/08 1 3 1 T4 WW 0,1101
Irrigation with wastewater
1 27/jun/08 1 4 1 T1 WW 0,0665
Irrigation with wastewater
1 27/jun/08 1 5 2 T1 WW 0,0675
Irrigation with wastewater
1 27/jun/08 1 6 2 T2 WW 0,0668
Irrigation with wastewater
1 3/jul/08 7 7 2 T3 WW 0,0718
Irrigation with wastewater
1 3/jul/08 7 8 2 T4 WW 0,0777
Irrigation with wastewater
1 3/jul/08 7 9 3 T4 WW 0,0982
Irrigation with wastewater
1 3/jul/08 7 10 3 T1 WW 0,065
Irrigation with wastewater
1 3/jul/08 7 11 3 T2 WW 0,081
Irrigation with wastewater
1 3/jul/08 7 12 3 T3 WW 0,0661
Irrigation with wastewater
2 7/jul/08 11 1 1 T3 WW 0,0935
Irrigation with wastewater
2 7/jul/08 11 2 1 T2 WW 0,0874
Irrigation with wastewater
2 7/jul/08 11 3 1 T4 WW 0,1273
Irrigation with wastewater
2 7/jul/08 11 4 1 T1 WW 0,0688
Irrigation with wastewater
2 7/jul/08 11 5 2 T1 WW 0,07
Irrigation with wastewater
2 7/jul/08 11 6 2 T2 WW 0,0686
Irrigation with wastewater
2 10/jul/08 14 7 2 T3 WW 0,0743
Irrigation with wastewater
2 10/jul/08 14 8 2 T4 WW 0,0774
Irrigation with wastewater
2 10/jul/08 14 9 3 T4 WW 0,0996
Irrigation with wastewater
2 10/jul/08 14 10 3 T1 WW 0,0593
Irrigation with wastewater
2 10/jul/08 14 11 3 T2 WW 0,0818
Irrigation with wastewater
2 10/jul/08 14 12 3 T3 WW 0,0658
Irrigation with wastewater
3 12/jul/08 16 1 1 T3 WW 0,0939
Irrigation with wastewater
3 12/jul/08 16 2 1 T2 WW 0,0884
Irrigation with wastewater
3 12/jul/08 16 3 1 T4 WW 0,1077
Irrigation with wastewater
3 12/jul/08 16 4 1 T1 WW 0,068
Irrigation with wastewater
3 12/jul/08 16 5 2 T1 WW 0,0683
Irrigation with wastewater
3 12/jul/08 16 6 2 T2 WW 0,0666
Irrigation with wastewater
3 12/jul/08 16 7 2 T3 WW 0,068
Irrigation with wastewater
3 16/jul/08 20 8 2 T4 WW 0,0739
Irrigation with wastewater
3 16/jul/08 20 9 3 T4 WW 0,1033
Irrigation with wastewater
3 16/jul/08 20 10 3 T1 WW 0,0594
Irrigation with wastewater
3 16/jul/08 20 11 3 T2 WW 0,0799
Irrigation with wastewater
3 16/jul/08 20 12 3 T3 WW 0,0623
Irrigation with wastewater
3,5 18/jul/08 22 1 1 T3 WW 0,0961
Irrigation with wastewater
3,5 18/jul/08 22 2 1 T2 WW 0,0911
Irrigation with wastewater
3,5 18/jul/08 22 3 1 T4 WW 0,1066
Irrigation with wastewater
3,5 18/jul/08 22 4 1 T1 WW 0,0715
Irrigation with wastewater
3,5 18/jul/08 22 5 2 T1 WW 0,0704
Irrigation with wastewater
3,5 18/jul/08 22 6 2 T2 WW 0,0685
Irrigation with wastewater
3,5 20/jul/08 24 7 2 T3 WW 0,068
Irrigation with wastewater
3,5 20/jul/08 24 8 2 T4 WW 0,0739
Irrigation with wastewater
3,5 20/jul/08 24 9 3 T4 WW 0,1033
Irrigation with wastewater
3,5 20/jul/08 24 10 3 T1 WW 0,0594
Irrigation with wastewater
3,5 20/jul/08 24 11 3 T2 WW 0,0799
Irrigation with wastewater
3,5 20/jul/08 24 12 3 T3 WW 0,0623
Irrigation with wastewater
4 23/jul/08 27 1 1 T3 WW 0,0767
Irrigation with wastewater
4 23/jul/08 27 2 1 T2 WW 0,0877
Irrigation with wastewater
4 23/jul/08 27 3 1 T4 WW 0,104
Irrigation with wastewater
4 23/jul/08 27 4 1 T1 WW 0,0593
Irrigation with wastewater
4 23/jul/08 27 5 2 T1 WW 0,0646
Irrigation with wastewater
4 23/jul/08 27 6 2 T2 WW 0,0668
Irrigation with wastewater
4 26/jul/08 30 7 2 T3 WW 0,0645
Irrigation with wastewater
4 26/jul/08 30 8 2 T4 WW 0,0705
Irrigation with wastewater
4 26/jul/08 30 9 3 T4 WW 0,0942
Irrigation with wastewater
4 26/jul/08 30 10 3 T1 WW 0,0553
Irrigation with wastewater
4 26/jul/08 30 11 3 T2 WW 0,0744
Irrigation with wastewater
4 26/jul/08 30 12 3 T3 WW 0,06
Irrigation with wastewater
4,5 30/jul/08 34 1 1 T3 WW 0,0764
Irrigation with wastewater
4,5 30/jul/08 34 2 1 T2 WW 0,0812
Irrigation with wastewater
4,5 30/jul/08 34 3 1 T4 WW 0,1011
Irrigation with wastewater
4,5 30/jul/08 34 4 1 T1 WW 0,0643
Irrigation with wastewater
4,5 30/jul/08 34 5 2 T1 WW 0,0673
Irrigation with wastewater
4,5 30/jul/08 34 6 2 T2 WW 0,064
Irrigation with wastewater
4,5 1/aug/08 36 7 2 T3 WW 0,0623
Irrigation with wastewater
4,5 1/aug/08 36 8 2 T4 WW 0,0646
Irrigation with wastewater
4,5 1/aug/08 36 9 3 T4 WW 0,0702
Irrigation with wastewater
4,5 1/aug/08 36 10 3 T1 WW 0,0531
Irrigation with wastewater
4,5 1/aug/08 36 11 3 T2 WW 0,0707
Irrigation with wastewater
4,5 1/aug/08 36 12 3 T3 WW 0,0619
Irrigation with wastewater
5 6/aug/08 41 1 1 T3 WW 0,0766
Irrigation with wastewater
5 6/aug/08 41 2 1 T2 WW 0,077
Irrigation with wastewater
5 6/aug/08 41 3 1 T4 WW 0,1022
Irrigation with wastewater
5 6/aug/08 41 4 1 T1 WW 0,0624
Irrigation with wastewater
5 6/aug/08 41 5 2 T1 WW 0,0615
Irrigation with wastewater
5 6/aug/08 41 6 2 T2 WW 0,061
Irrigation with wastewater
5 9/aug/08 44 7 2 T3 WW 0,0594
Irrigation with wastewater
5 9/aug/08 44 8 2 T4 WW 0,0709
Irrigation with wastewater
5 9/aug/08 44 9 3 T4 WW 0,0787
Irrigation with wastewater
5 9/aug/08 44 10 3 T1 WW 0,0523
Irrigation with wastewater
5 9/aug/08 44 11 3 T2 WW 0,0778
Irrigation with wastewater
5 9/aug/08 44 12 3 T3 WW 0,0626
Irrigation with wastewater
6 11/aug/08 46 1 1 T3 WW 0,0702
Irrigation with wastewater
6 11/aug/08 46 2 1 T2 WW 0,0787
Irrigation with wastewater
6 11/aug/08 46 3 1 T4 WW 0,1035
Irrigation with wastewater
6 11/aug/08 46 4 1 T1 WW 0,0607
Irrigation with wastewater
6 11/aug/08 46 5 2 T1 WW 0,0617
Irrigation with wastewater
6 11/aug/08 46 6 2 T2 WW 0,0613
Irrigation with wastewater
6 13/aug/08 48 7 2 T3 WW 0,0616
Irrigation with wastewater
6 13/aug/08 48 8 2 T4 WW 0,0649
Irrigation with wastewater
6 13/aug/08 48 9 3 T4 WW 0,0737
Irrigation with wastewater
6 13/aug/08 48 10 3 T1 WW 0,0534
Irrigation with wastewater
6 13/aug/08 48 11 3 T2 WW 0,0777
Irrigation with wastewater
6 13/aug/08 48 12 3 T3 WW 0,0675
Irrigation with wastewater
6,5 15/aug/08 50 1 1 T3 WW 0,0728
Irrigation with wastewater
6,5 15/aug/08 50 2 1 T2 WW 0,074
Irrigation with wastewater
6,5 15/aug/08 50 3 1 T4 WW 0,0968
Irrigation with wastewater
6,5 15/aug/08 50 4 1 T1 WW 0,0629
Irrigation with wastewater
6,5 15/aug/08 50 5 2 T1 WW 0,0602
Irrigation with wastewater
6,5 15/aug/08 50 6 2 T2 WW 0,0596
Irrigation with wastewater
6,5 16/aug/08 51 7 2 T3 WW 0,0633
Irrigation with wastewater
6,5 16/aug/08 51 8 2 T4 WW 0,0678
Irrigation with wastewater
6,5 16/aug/08 51 9 3 T4 WW 0,09
Irrigation with wastewater
6,5 16/aug/08 51 10 3 T1 WW 0,0545
Irrigation with wastewater
6,5 16/aug/08 51 11 3 T2 WW 0,0745
Irrigation with wastewater
6,5 16/aug/08 51 12 3 T3 WW 0,0673
Irrigation with wastewater
7 20/aug/08 55 1 1 T3 WW 0,079
Irrigation with wastewater
7 20/aug/08 55 2 1 T2 WW 0,0802
Irrigation with wastewater
7 20/aug/08 55 3 1 T4 WW 0,0995
Irrigation with wastewater
7 20/aug/08 55 4 1 T1 WW 0,0596
Irrigation with wastewater
7 20/aug/08 55 5 2 T1 WW 0,0662
Irrigation with wastewater
7 20/aug/08 55 6 2 T2 WW 0,0606
Irrigation with wastewater
7 23/aug/08 58 7 2 T3 WW 0,0617
Irrigation with wastewater
7 23/aug/08 58 8 2 T4 WW 0,0684
Irrigation with wastewater
7 23/aug/08 58 9 3 T4 WW 0,09
Irrigation with wastewater
7 23/aug/08 58 10 3 T1 WW 0,054
Irrigation with wastewater
7 23/aug/08 58 11 3 T2 WW 0,0782
Irrigation with wastewater
7 23/aug/08 58 12 3 T3 WW 0,0548
Irrigation with wastewater
7,5 26/aug/08 61 1 1 T3 WW 0,0775
Irrigation with wastewater
7,5 26/aug/08 61 2 1 T2 WW 0,0767
Irrigation with wastewater
7,5 26/aug/08 61 3 1 T4 WW 0,1102
Irrigation with wastewater
7,5 26/aug/08 61 4 1 T1 WW 0,0691
Irrigation with wastewater
7,5 26/aug/08 61 5 2 T1 WW 0,0654
Irrigation with wastewater
7,5 26/aug/08 61 6 2 T2 WW 0,0662
Irrigation with wastewater
7,5 28/aug/08 63 7 2 T3 WW 0,0684
Irrigation with wastewater
7,5 28/aug/08 63 8 2 T4 WW 0,0674
Irrigation with wastewater
7,5 28/aug/08 63 9 3 T4 WW 0,0936
Irrigation with wastewater
7,5 28/aug/08 63 10 3 T1 WW 0,055
Irrigation with wastewater
7,5 28/aug/08 63 11 3 T2 WW 0,0751
Irrigation with wastewater
7,5 28/aug/08 63 12 3 T3 WW 0,0651
Irrigation with wastewater
8 4/sep/08 70 1 1 T3 WW 0,0839
Irrigation with wastewater
8 4/sep/08 70 2 1 T2 WW 0,0841
Irrigation with wastewater
8 4/sep/08 70 3 1 T4 WW 0,1073
Irrigation with wastewater
8 4/sep/08 70 4 1 T1 WW 0,0661
Irrigation with wastewater
8 4/sep/08 70 5 2 T1 WW 0,0668
Irrigation with wastewater
8 4/sep/08 70 6 2 T2 WW 0,0734
Irrigation with wastewater
8 9/sep/08 75 7 2 T3 WW 0,0699
Irrigation with wastewater
8 9/sep/08 75 8 2 T4 WW 0,0729
Irrigation with wastewater
8 9/sep/08 75 9 3 T4 WW 0,1004
Irrigation with wastewater
8 9/sep/08 75 10 3 T1 WW 0,0569
Irrigation with wastewater
8 9/sep/08 75 11 3 T2 WW 0,0748
Irrigation with wastewater
8 9/sep/08 75 12 3 T3 WW 0,0636
Irrigation with wastewater
9 15/sep/08 81 1 1 T3 DW 0,091
Irrigation with diminirize water
9 15/sep/08 81 2 1 T2 DW 0,0952
Irrigation with diminirize water
9 15/sep/08 81 3 1 T4 DW 0,1135
Irrigation with diminirize water
9 15/sep/08 81 4 1 T1 DW 0,0839
Irrigation with diminirize water
9 15/sep/08 81 5 2 T1 DW 0,0758
Irrigation with diminirize water
9 15/sep/08 81 6 2 T2 DW 0,0684
Irrigation with diminirize water
9 21/sep/08 87 7 2 T3 DW 0,0965
Irrigation with diminirize water
9 21/sep/08 87 8 2 T4 DW 0,0887
Irrigation with diminirize water
9 21/sep/08 87 9 3 T4 DW 0,1028
Irrigation with diminirize water
9 21/sep/08 87 10 3 T1 DW 0,071
Irrigation with diminirize water
9 21/sep/08 87 11 3 T2 DW 0,0712
Irrigation with diminirize water
9 21/sep/08 87 12 3 T3 DW 0,0639
Irrigation with diminirize water
10 2/okt/08 98 1 1 T3 DW 0,092
Irrigation with diminirize water
10 2/okt/08 98 2 1 T2 DW 0,0895
Irrigation with diminirize water
10 2/okt/08 98 3 1 T4 DW 0,1051
Irrigation with diminirize water
10 2/okt/08 98 4 1 T1 DW 0,0768
Irrigation with diminirize water
10 2/okt/08 98 5 2 T1 DW 0,0732
Irrigation with diminirize water
10 2/okt/08 98 6 2 T2 DW 0,072
Irrigation with diminirize water
10 7/okt/08 103 7 2 T3 DW 0,079
Irrigation with diminirize water
10 7/okt/08 103 8 2 T4 DW 0,0684
Irrigation with diminirize water
10 7/okt/08 103 9 3 T4 DW 0,1038
Irrigation with diminirize water
10 7/okt/08 103 10 3 T1 DW 0,074
Irrigation with diminirize water
10 7/okt/08 103 11 3 T2 DW 0,0699
Irrigation with diminirize water
10 7/okt/08 103 12 3 T3 DW 0,0659
Irrigation with diminirize water
11 10/okt/08 106 1 1 T3 DW 0,091
Irrigation with diminirize water
11 10/okt/08 106 2 1 T2 DW 0,087
Irrigation with diminirize water
11 10/okt/08 106 3 1 T4 DW 0,105
Irrigation with diminirize water
11 10/okt/08 106 4 1 T1 DW 0,0776
Irrigation with diminirize water
11 10/okt/08 106 5 2 T1 DW 0,071
Irrigation with diminirize water
11 10/okt/08 106 6 2 T2 DW 0,0692
Irrigation with diminirize water
11 14/okt/08 110 7 2 T3 DW 0,08
Irrigation with diminirize water
11 14/okt/08 110 8 2 T4 DW 0,0514
Irrigation with diminirize water
11 14/okt/08 110 9 3 T4 DW 0,1012
Irrigation with diminirize water
11 14/okt/08 110 10 3 T1 DW 0,0625
Irrigation with diminirize water
11 14/okt/08 110 11 3 T2 DW 0,0689
Irrigation with diminirize water
11 14/okt/08 110 12 3 T3 DW 0,0649
Irrigation with diminirize water
12 18/okt/08 114 1 1 T3 DW 0,096
Irrigation with diminirize water
12 18/okt/08 114 2 1 T2 DW 0,093
Irrigation with diminirize water
12 18/okt/08 114 3 1 T4 DW 0,1084
Irrigation with diminirize water
12 18/okt/08 114 4 1 T1 DW 0,0756
Irrigation with diminirize water
12 18/okt/08 114 5 2 T1 DW 0,0681
Irrigation with diminirize water
12 18/okt/08 114 6 2 T2 DW 0,0689
Irrigation with diminirize water
12 23/okt/08 119 7 2 T3 DW 0,077
Irrigation with diminirize water
12 23/okt/08 119 8 2 T4 DW 0,0614
Irrigation with diminirize water
12 23/okt/08 119 9 3 T4 DW 0,0999
Irrigation with diminirize water
12 23/okt/08 119 10 3 T1 DW 0,0585
Irrigation with diminirize water
12 23/okt/08 119 11 3 T2 DW 0,0681
Irrigation with diminirize water
12 23/okt/08 119 12 3 T3 DW 0,0629
Irrigation with diminirize water
----------------------------------------------------------------------------------------------
> mod <- aov(ThetaV ~ factor(Block) + Treatmen:factor(Week))
> anova(mod)
Analysis of Variance Table
Response: ThetaV
Df Sum Sq Mean Sq F value Pr(>F)
factor(Block) 2 0.0073713 0.0036856 49.4955 2.074e-15 ***
Treatmen:factor(Week) 47 0.0168852 0.0003593 4.8246 4.606e-11 ***
Residuals 94 0.0069996 0.0000745
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> mod <- aov(ThetaV ~ factor(Block) + Treatmen*factor(Week))
> anova(mod)
Analysis of Variance Table
Response: ThetaV
Df Sum Sq Mean Sq F value Pr(>F)
factor(Block) 2 0.0073713 0.0036856 49.4955 2.074e-15 ***
Treatmen 3 0.0139313 0.0046438 62.3627 < 2.2e-16 ***
factor(Week) 11 0.0024297 0.0002209 2.9663 0.002038 **
Treatmen:factor(Week) 33 0.0005242 0.0000159 0.2133 0.999998
Residuals 94 0.0069996 0.0000745
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> TukeyHSD(mod,"Treatmen")
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = ThetaV ~ factor(Block) + Treatmen * factor(Week))
$Treatmen
diff lwr upr p adj
T2-T1 0.012650000 0.007330061 0.0179699388 0.0000001
T3-T1 0.008130556 0.002810617 0.0134504943 0.0007251
T4-T1 0.027086111 0.021766172 0.0324060499 0.0000000
T3-T2 -0.004519444 -0.009839383 0.0008004943 0.1247735
T4-T2 0.014436111 0.009116172 0.0197560499 0.0000000
T4-T3 0.018955556 0.013635617 0.0242754943 0.0000000
> tapply(ThetaV,Treatmen,mean)
T1 T2 T3 T4
0.06240833 0.07505833 0.07053889 0.08949444
> tapply(NoThetaV,Week,mean)
1 2 3 4 5 6 7
0.07895000 0.08115000 0.07830833 0.07925000 0.07316667 0.06975833 0.07020000
8 9 10 11 12
0.06957500 0.07030833 0.07101667 0.07414167 0.07667500
> tapply(ThetaV,list(Week,Treatmen),mean)
T1 T2 T3 T4
1 0.06633333 0.07806667 0.07606667 0.09533333
2 0.06603333 0.07926667 0.07786667 0.10143333
3 0.06523333 0.07830000 0.07473333 0.09496667
4 0.06710000 0.07983333 0.07546667 0.09460000
5 0.05973333 0.07630000 0.06706667 0.08956667
6 0.06156667 0.07196667 0.06686667 0.07863333
7 0.05873333 0.07193333 0.06620000 0.08393333
8 0.05860000 0.07256667 0.06643333 0.08070000
9 0.05920000 0.06936667 0.06780000 0.08486667
10 0.05993333 0.07300000 0.06516667 0.08596667
11 0.06316667 0.07266667 0.07033333 0.09040000
12 0.06326667 0.07743333 0.07246667 0.09353333
> _____________________________________________________________________________________________
> RBF <- aov(ThetaExpT$ThetaV ~ factor(ThetaExpT$Block) +
> factor(ThetaExpT$Week):factor(ThetaExpT$Treatment) )
> anova(RBF)
Analysis of Variance Table
Response: ThetaExpT$ThetaV
Df Sum Sq Mean Sq
factor(ThetaExpT$Block) 2 0.0108151 0.0054075
factor(ThetaExpT$Week):factor(ThetaExpT$Treatment) 63 0.0215197 0.0003416
Residuals 126 0.0112558 0.0000893
F value Pr(>F)
factor(ThetaExpT$Block) 60.5330 < 2.2e-16 ***
factor(ThetaExpT$Week):factor(ThetaExpT$Treatment) 3.8237 7.783e-11 ***
Residuals
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> RBF <- aov(ThetaExpT$ThetaV ~ factor(ThetaExpT$Block) +
> factor(ThetaExpT$Week)*factor(ThetaExpT$Treatment) )
> anova(RBF)
Analysis of Variance Table
Response: ThetaExpT$ThetaV
Df Sum Sq Mean Sq
factor(ThetaExpT$Block) 2 0.0108151 0.0054075
factor(ThetaExpT$Week) 15 0.0041717 0.0002781
factor(ThetaExpT$Treatment) 3 0.0161244 0.0053748
factor(ThetaExpT$Week):factor(ThetaExpT$Treatment) 45 0.0012236 0.0000272
Residuals 126 0.0112558 0.0000893
F value Pr(>F)
factor(ThetaExpT$Block) 60.5330 < 2.2e-16 ***
factor(ThetaExpT$Week) 3.1133 0.0002501 ***
factor(ThetaExpT$Treatment) 60.1665 < 2.2e-16 ***
factor(ThetaExpT$Week):factor(ThetaExpT$Treatment) 0.3044 0.9999915
Residuals
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> TukeyHSD(RBF,"Treatment")
Error in TukeyHSD.aov(RBF, "Treatment") : 'which' specified no factors
> TukeyHSD(RBF,"factor(ThetaExpT$Treatment)")
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = ThetaExpT$ThetaV ~ factor(ThetaExpT$Block) +
factor(ThetaExpT$Week) * factor(ThetaExpT$Treatment))
$`factor(ThetaExpT$Treatment)`
diff lwr upr p adj
T2-T1 0.010597917 0.005574723 0.015621111 0.0000012
T3-T1 0.008016667 0.002993473 0.013039861 0.0003436
T4-T1 0.025347917 0.020324723 0.030371111 0.0000000
T3-T2 -0.002581250 -0.007604444 0.002441944 0.5406528
T4-T2 0.014750000 0.009726806 0.019773194 0.0000000
T4-T3 0.017331250 0.012308056 0.022354444 0.0000000
> TukeyHSD(RBF,"factor(ThetaExpT$Week)")
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = ThetaExpT$ThetaV ~ factor(ThetaExpT$Block) +
factor(ThetaExpT$Week) * factor(ThetaExpT$Treatment))
$`factor(ThetaExpT$Week)`
diff lwr upr p adj
2-1 0.0022000000 -0.0112915964 0.015691596 0.9999999
3-1 -0.0006416667 -0.0141332631 0.012849930 1.0000000
3.5-1 0.0003000000 -0.0131915964 0.013791596 1.0000000
4-1 -0.0057833333 -0.0192749297 0.007708263 0.9807680
4.5-1 -0.0091916667 -0.0226832631 0.004299930 0.5643712
5-1 -0.0087500000 -0.0222415964 0.004741596 0.6477289
6-1 -0.0093750000 -0.0228665964 0.004116596 0.5295103
6.5-1 -0.0086416667 -0.0221332631 0.004849930 0.6677096
7-1 -0.0079333333 -0.0214249297 0.005558263 0.7884928
7.5-1 -0.0048083333 -0.0182999297 0.008683263 0.9969774
8-1 -0.0022750000 -0.0157665964 0.011216596 0.9999998
9-1 0.0062083333 -0.0072832631 0.019699930 0.9638857
10-1 0.0018500000 -0.0116415964 0.015341596 1.0000000
11-1 -0.0014750000 -0.0149665964 0.012016596 1.0000000
12-1 -0.0008000000 -0.0142915964 0.012691596 1.0000000
3-2 -0.0028416667 -0.0163332631 0.010649930 0.9999952
3.5-2 -0.0019000000 -0.0153915964 0.011591596 1.0000000
4-2 -0.0079833333 -0.0214749297 0.005508263 0.7806960
4.5-2 -0.0113916667 -0.0248832631 0.002099930 0.2052535
5-2 -0.0109500000 -0.0244415964 0.002541596 0.2621502
6-2 -0.0115750000 -0.0250665964 0.001916596 0.1843734
6.5-2 -0.0108416667 -0.0243332631 0.002649930 0.2775172
7-2 -0.0101333333 -0.0236249297 0.003358263 0.3905650
7.5-2 -0.0070083333 -0.0204999297 0.006483263 0.9058749
8-2 -0.0044750000 -0.0179665964 0.009016596 0.9986299
9-2 0.0040083333 -0.0094832631 0.017499930 0.9996182
10-2 -0.0003500000 -0.0138415964 0.013141596 1.0000000
11-2 -0.0036750000 -0.0171665964 0.009816596 0.9998671
12-2 -0.0030000000 -0.0164915964 0.010491596 0.9999901
3.5-3 0.0009416667 -0.0125499297 0.014433263 1.0000000
4-3 -0.0051416667 -0.0186332631 0.008349930 0.9938879
4.5-3 -0.0085500000 -0.0220415964 0.004941596 0.6843839
5-3 -0.0081083333 -0.0215999297 0.005383263 0.7606483
6-3 -0.0087333333 -0.0222249297 0.004758263 0.6508201
6.5-3 -0.0080000000 -0.0214915964 0.005491596 0.7780682
7-3 -0.0072916667 -0.0207832631 0.006199930 0.8756776
7.5-3 -0.0041666667 -0.0176582631 0.009324930 0.9993965
8-3 -0.0016333333 -0.0151249297 0.011858263 1.0000000
9-3 0.0068500000 -0.0066415964 0.020341596 0.9204690
10-3 0.0024916667 -0.0109999297 0.015983263 0.9999992
11-3 -0.0008333333 -0.0143249297 0.012658263 1.0000000
12-3 -0.0001583333 -0.0136499297 0.013333263 1.0000000
4-3.5 -0.0060833333 -0.0195749297 0.007408263 0.9697055
4.5-3.5 -0.0094916667 -0.0229832631 0.003999930 0.5074372
5-3.5 -0.0090500000 -0.0225415964 0.004441596 0.5913084
6-3.5 -0.0096750000 -0.0231665964 0.003816596 0.4731081
6.5-3.5 -0.0089416667 -0.0224332631 0.004549930 0.6118196
7-3.5 -0.0082333333 -0.0217249297 0.005258263 0.7398602
7.5-3.5 -0.0051083333 -0.0185999297 0.008383263 0.9942829
8-3.5 -0.0025750000 -0.0160665964 0.010916596 0.9999987
9-3.5 0.0059083333 -0.0075832631 0.019399930 0.9766245
10-3.5 0.0015500000 -0.0119415964 0.015041596 1.0000000
11-3.5 -0.0017750000 -0.0152665964 0.011716596 1.0000000
12-3.5 -0.0011000000 -0.0145915964 0.012391596 1.0000000
4.5-4 -0.0034083333 -0.0168999297 0.010083263 0.9999484
5-4 -0.0029666667 -0.0164582631 0.010524930 0.9999915
6-4 -0.0035916667 -0.0170832631 0.009899930 0.9999001
6.5-4 -0.0028583333 -0.0163499297 0.010633263 0.9999948
7-4 -0.0021500000 -0.0156415964 0.011341596 0.9999999
7.5-4 0.0009750000 -0.0125165964 0.014466596 1.0000000
8-4 0.0035083333 -0.0099832631 0.016999930 0.9999255
9-4 0.0119916667 -0.0014999297 0.025483263 0.1427516
10-4 0.0076333333 -0.0058582631 0.021124930 0.8323616
11-4 0.0043083333 -0.0091832631 0.017799930 0.9991104
12-4 0.0049833333 -0.0085082631 0.018474930 0.9955808
5-4.5 0.0004416667 -0.0130499297 0.013933263 1.0000000
6-4.5 -0.0001833333 -0.0136749297 0.013308263 1.0000000
6.5-4.5 0.0005500000 -0.0129415964 0.014041596 1.0000000
7-4.5 0.0012583333 -0.0122332631 0.014749930 1.0000000
7.5-4.5 0.0043833333 -0.0091082631 0.017874930 0.9989162
8-4.5 0.0069166667 -0.0065749297 0.020408263 0.9145216
9-4.5 0.0154000000 0.0019084036 0.028891596 0.0102437
10-4.5 0.0110416667 -0.0024499297 0.024533263 0.2495770
11-4.5 0.0077166667 -0.0057749297 0.021208263 0.8206976
12-4.5 0.0083916667 -0.0050999297 0.021883263 0.7125787
6-5 -0.0006250000 -0.0141165964 0.012866596 1.0000000
6.5-5 0.0001083333 -0.0133832631 0.013599930 1.0000000
7-5 0.0008166667 -0.0126749297 0.014308263 1.0000000
7.5-5 0.0039416667 -0.0095499297 0.017433263 0.9996876
8-5 0.0064750000 -0.0070165964 0.019966596 0.9487494
9-5 0.0149583333 0.0014667369 0.028449930 0.0151166
10-5 0.0106000000 -0.0028915964 0.024091596 0.3137269
11-5 0.0072750000 -0.0062165964 0.020766596 0.8775993
12-5 0.0079500000 -0.0055415964 0.021441596 0.7859085
6.5-6 0.0007333333 -0.0127582631 0.014224930 1.0000000
7-6 0.0014416667 -0.0120499297 0.014933263 1.0000000
7.5-6 0.0045666667 -0.0089249297 0.018058263 0.9982809
8-6 0.0071000000 -0.0063915964 0.020591596 0.8966805
9-6 0.0155833333 0.0020917369 0.029074930 0.0086842
10-6 0.0112250000 -0.0022665964 0.024716596 0.2256286
11-6 0.0079000000 -0.0055915964 0.021391596 0.7936171
12-6 0.0085750000 -0.0049165964 0.022066596 0.6798597
7-6.5 0.0007083333 -0.0127832631 0.014199930 1.0000000
7.5-6.5 0.0038333333 -0.0096582631 0.017324930 0.9997770
8-6.5 0.0063666667 -0.0071249297 0.019858263 0.9553666
9-6.5 0.0148500000 0.0013584036 0.028341596 0.0165983
10-6.5 0.0104916667 -0.0029999297 0.023983263 0.3307898
11-6.5 0.0071666667 -0.0063249297 0.020658263 0.8896480
12-6.5 0.0078416667 -0.0056499297 0.021333263 0.8024391
7.5-7 0.0031250000 -0.0103665964 0.016616596 0.9999831
8-7 0.0056583333 -0.0078332631 0.019149930 0.9843135
9-7 0.0141416667 0.0006500703 0.027633263 0.0299922
10-7 0.0097833333 -0.0037082631 0.023274930 0.4531110
11-7 0.0064583333 -0.0070332631 0.019949930 0.9498107
12-7 0.0071333333 -0.0063582631 0.020624930 0.8932006
8-7.5 0.0025333333 -0.0109582631 0.016024930 0.9999990
9-7.5 0.0110166667 -0.0024749297 0.024508263 0.2529667
10-7.5 0.0066583333 -0.0068332631 0.020149930 0.9359982
11-7.5 0.0033333333 -0.0101582631 0.016824930 0.9999611
12-7.5 0.0040083333 -0.0094832631 0.017499930 0.9996182
9-8 0.0084833333 -0.0050082631 0.021974930 0.6963560
10-8 0.0041250000 -0.0093665964 0.017616596 0.9994636
11-8 0.0008000000 -0.0126915964 0.014291596 1.0000000
12-8 0.0014750000 -0.0120165964 0.014966596 1.0000000
10-9 -0.0043583333 -0.0178499297 0.009133263 0.9989846
11-9 -0.0076833333 -0.0211749297 0.005808263 0.8254130
12-9 -0.0070083333 -0.0204999297 0.006483263 0.9058749
11-10 -0.0033250000 -0.0168165964 0.010166596 0.9999624
12-10 -0.0026500000 -0.0161415964 0.010841596 0.9999981
12-11 0.0006750000 -0.0128165964 0.014166596 1.0000000
>
___________________________________________________________________________________________
library(RODBC)
canal <- odbcConnectExcel("final_results_Oxct08")
A<- sqlFetch(canal,"A")
odbcCloseAll()
str(A)
model <- lm(ThetaV ~ Block + Treatment + condition, data = A)
residual<-residuals(model)
# Only efect time
model2 <- lm(residual ~ DateBTC, data=A)
summary(model2)
# Other case
model3 <- lm(ThetaV ~ Treatment, data = A)
summary(model3)
model4 <- lm(ThetaV ~ condition+DateBTC, data = A)
summary(model4)
model5 <- lm(ThetaV ~ condition, data = A)
summary(model5)
--------------------------------------------------------------------------------------------------
In this particular case, the fixed-effect model and the RCB
design will give the same p-values:
bad.aov <- aov(ThetaV ~ Treatment + Block, data=table)
summary(bad.aov)
------------------------------------------------------------------
library(nlme)
m2 = lme(ThetaV ~ Treatment, random = ~1|Block, data=table)
anova(m2)
detach("package:nlme")
library(lme4)
m3 = lmer(ThetaV ~ Treatment+(1|Block), data=table)
anova(m3)
--------------------------------------------------------------------------------------------------
library(lme4)
water<-read.csv("locationofattachedfile",header=T)
attach(water)
model<-lmer(ThetaV~trt+(block|trt)+week+condition,data=water)
model
anova(model)
------------------------------------------------------------------------------------------------
alis.lme=lme(fixed=response~treatment-1 + time +
time*treatment,data=alis.grDat,random=~1|Block)
summary(alis.lme)
--------------------------------------------------------------------------------------------------------
--
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