[R] unbalanced effects in aov
Brooke LaFlamme
bal44 at cornell.edu
Fri Sep 14 21:18:34 CEST 2007
Hi, I have been having some trouble using aov to do an anova, probably because I'm not understanding how to use this function correctly. For some reason it always tells me that "Estimated effects may be unbalanced", though I'm not sure what this means. Is the formula I am using written incorrectly? Below is the code I am using along with the data:
> my.data
response species sex line replicate plate
1 -7.092854e-03 1 1 1 1 1
2 -8.663481e-04 1 2 1 1 1
3 -5.797276e-03 1 1 2 1 1
4 -2.598078e-03 1 2 2 1 1
5 7.832551e-04 2 1 1 1 1
6 1.333361e-03 2 2 1 1 1
7 -8.972490e-04 2 1 2 1 1
8 -2.834589e-03 2 2 2 1 1
9 5.655464e-04 3 1 1 1 1
10 7.371403e-03 3 2 1 1 1
11 3.160040e-03 3 1 2 1 1
12 -4.110653e-03 1 1 2 2 2
13 -2.262314e-03 1 2 2 2 2
14 -3.259483e-03 1 1 3 1 2
15 -5.671712e-03 1 2 3 1 2
16 -3.636077e-03 2 1 2 2 2
17 -3.904864e-03 2 2 2 2 2
18 1.025440e-03 2 1 3 1 2
19 -3.789292e-03 2 2 3 1 2
20 3.396270e-03 3 1 2 2 2
21 8.807778e-03 3 2 2 2 2
22 5.456604e-03 3 2 3 1 2
23 -1.134216e-02 1 1 3 2 3
24 -7.725740e-03 1 2 3 2 3
25 -1.589719e-03 1 1 4 1 3
26 4.574659e-04 1 2 4 1 3
27 -2.899983e-03 2 1 3 2 3
28 -4.310185e-03 2 2 3 2 3
29 -3.200475e-05 2 1 4 1 3
30 3.166308e-03 3 1 3 2 3
31 5.697712e-03 3 2 3 2 3
32 6.058486e-03 3 1 4 1 3
33 6.941016e-03 3 2 4 1 3
34 -2.794982e-03 1 1 4 2 4
35 -4.416711e-03 1 1 5 1 4
36 -4.062832e-03 1 2 5 1 4
37 1.763941e-03 2 1 4 2 4
38 -2.928930e-03 2 2 4 2 4
39 -2.869975e-03 2 2 5 1 4
40 6.949621e-03 3 1 4 2 4
41 5.766447e-03 3 2 4 2 4
42 2.510278e-03 3 1 5 1 4
43 5.507496e-03 3 2 5 1 4
44 -1.197325e-02 1 2 5 2 5
45 -6.556955e-03 1 1 6 1 5
46 3.622169e-04 2 1 5 2 5
47 -1.288784e-03 2 2 5 2 5
48 -2.863541e-03 2 1 6 1 5
49 -7.082933e-03 2 2 6 1 5
50 3.813700e-03 3 1 5 2 5
51 9.593295e-03 3 2 5 2 5
52 9.881930e-03 3 2 6 1 5
53 -1.081725e-02 1 1 6 2 6
54 -8.870041e-03 1 2 6 2 6
55 -5.305931e-04 1 2 7 1 6
56 2.835570e-03 2 1 6 2 6
57 4.541555e-03 2 2 6 2 6
58 -5.909101e-03 2 1 7 1 6
59 -2.768342e-03 2 2 7 1 6
60 8.835976e-03 3 1 6 2 6
61 1.234038e-02 3 2 6 2 6
62 2.015527e-03 3 1 7 1 6
63 6.485565e-03 3 2 7 1 6
64 -8.372922e-03 1 1 7 2 7
65 -9.439749e-03 1 2 7 2 7
66 -3.782672e-03 1 1 8 1 7
67 -2.576470e-03 1 2 8 1 7
68 2.878789e-03 2 1 7 2 7
69 -9.458139e-04 2 2 7 2 7
70 -3.993852e-03 2 2 8 1 7
71 5.997718e-03 3 1 7 2 7
72 -9.595505e-05 3 1 8 1 7
73 8.167411e-03 3 2 8 1 7
74 -1.181158e-02 1 1 8 2 8
75 -1.072585e-02 1 2 8 2 8
76 -2.856532e-03 1 1 9 1 8
77 -4.944013e-03 1 2 9 1 8
78 2.558783e-03 2 1 8 2 8
79 3.393314e-03 2 2 8 2 8
80 -4.466758e-03 2 1 9 1 8
81 -5.667622e-03 2 2 9 1 8
82 7.491253e-03 3 2 8 2 8
83 4.380724e-03 3 1 9 1 8
84 2.827233e-03 3 2 9 1 8
85 -7.433928e-03 1 2 9 2 9
86 -9.177664e-03 1 1 10 1 9
87 -6.040020e-04 1 2 10 1 9
88 1.394224e-03 2 1 9 2 9
89 -7.455449e-04 2 1 10 1 9
90 -2.251806e-03 2 2 10 1 9
91 7.865773e-03 3 1 9 2 9
92 6.287781e-03 3 2 9 2 9
93 7.734405e-03 3 1 10 1 9
94 9.757342e-03 3 2 10 1 9
95 -6.876948e-03 1 1 1 2 10
96 -4.974144e-03 1 2 1 2 10
97 -2.959226e-03 1 1 10 2 10
98 8.058296e-04 1 2 10 2 10
99 5.314729e-03 2 1 1 2 10
100 1.251126e-03 2 2 1 2 10
101 4.012311e-03 2 2 10 2 10
102 3.479155e-03 3 1 1 2 10
103 1.144813e-02 3 2 1 2 10
104 4.090214e-03 3 1 10 2 10
105 5.196910e-03 3 2 10 2 10
106 -9.038264e-03 1 2 6 1 11
107 -6.184877e-03 1 1 7 1 11
108 4.255164e-03 2 2 4 1 11
109 8.291281e-03 2 1 5 1 11
110 -5.368315e-04 2 2 9 2 11
111 -7.792906e-04 2 1 10 2 11
112 6.312335e-03 3 1 3 1 11
113 1.243561e-02 3 2 7 2 11
114 6.223999e-04 3 1 8 2 11
115 -6.517484e-03 1 2 4 2 12
116 -1.009622e-02 1 1 5 2 12
117 -4.414381e-04 1 1 9 2 12
118 2.221470e-03 2 1 8 1 12
119 1.041818e-02 3 2 2 1 12
120 3.384938e-04 3 1 6 1 12
I am treating all the variables as factors (except for response, obviously).
formula<-response~species+line%in%species+replicate%in%line+sex%in%species+plate
model<-aov(formula, data=my.data)
This is the output:
> model
Call:
aov(formula = formula, data = my.data)
Terms:
species plate species:line line:replicate
Sum of Squares 0.0026469288 0.0000945202 0.0003320255 0.0002008000
Deg. of Freedom 2 11 27 10
species:sex Residuals
Sum of Squares 0.0001383116 0.0006315465
Deg. of Freedom 3 66
Residual standard error: 0.003093362
Estimated effects may be unbalanced
Any help would be greatly appreciated as the R help documentation for aov does not address this issue.
Thanks!
--
Brooke LaFlamme
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