Hi! I'm using the limma package to analyze 2^3 factorial experiment, with blocks, but I've run into problems because lmFit can't estimate all coefficients. Here is what the design matrix looks like:

> design
   Intercept wt    A    B    C     AB    AC    BC     ABC block
1          1  1    0    0    0     0     0     0      0     1
2          1  0    1    0    0     0     0     0      0     1
3          1  0    0    1    0     0     0     0      0     1
4          1  0    0    0    1     0     0     0      0     1
5          1  0    0    0    0     1     0     0      0     0
6          1  0    0    0    0     0     1     0      0     0
7          1  0    0    0    0     0     0     1      0     0
8          1  0    0    0    0     0     0     0      1     0
9          1  1    0    0    0     0     0     0      0     0
10         1  0    1    0    0     0     0     0      0     0
11         1  0    0    1    0     0     0     0      0     0
12         1  0    0    0    1     0     0     0      0     0
13         1  0    0    0    0     1     0     0      0     0
14         1  0    0    0    0     0     1     0      0     0
15         1  0    0    0    0     0     0     1      0     0
16         1  0    0    0    0     0     0     0      1     0
17         1  1    0    0    0     0     0     0      0     0
18         1  0    1    0    0     0     0     0      0     0
19         1  0    0    1    0     0     0     0      0     0
20         1  0    0    0    1     0     0     0      0     0
21         1  0    0    0    0     1     0     0      0     0
22         1  0    0    0    0     0     1     0      0     0
23         1  0    0    0    0     0     0     1      0     0
24         1  0    0    0    0     0     0     0      1     0
attr(,"assign")
 [1] 0 1 1 1 1 1 1 1 1 1
attr(,"contrasts")
attr(,"contrasts")$treatments
        Wt    A    B    C     AB    AC    BC     ABC Block
bl1      1    0    0    0     0     0     0      0     1
Abl1     0    1    0    0     0     0     0      0     1
Bbl1     0    0    1    0     0     0     0      0     1
Cbl1     0    0    0    1     0     0     0      0     1
ABbl0    0    0    0    0     1     0     0      0     0
ACbl0    0    0    0    0     0     1     0      0     0
BCbl0    0    0    0    0     0     0     1      0     0
ABCbl0   0    0    0    0     0     0     0      1     0
bl0      1    0    0    0     0     0     0      0     0
Abl0     0    1    0    0     0     0     0      0     0
Bbl0     0    0    1    0     0     0     0      0     0
Cbl0     0    0    0    1     0     0     0      0     0
Cbl0II   0    0    0    1     0     0     0      0     0

Fitting a model to this with lmFit gives:

> fit <- lmFit(M.vals, design)
Coefficients not estimable: ABC

What is the problem with this? And what's the easisest way around it?

thanks

Jakub Orzechowski




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