Dears useRs,

I have 2 factors, (for the sake of explanation - A and B), with 4 levels each. I've already fitted a negative binomial generalized linear model to my data, and now I need to split the factors in two distinct analysis of deviance table:
 - A within B1, A within B2, A within B3 and A within B4
 - B within A1, B within A2, B within A3 and B within A4

Here is a code that illustrates my problem:

# inputing my data

require(MASS)

my.data <- data.frame("A"=rep(c(rep("Alevel1",4),rep("Alevel2",4),rep("Alevel3",4),rep("Alevel4",4)),4),
                      "B"=c(rep("Blevel1",16),rep("Blevel2",16),rep("Blevel3",16),rep("Blevel4",16)),
                      "value"=rnegbin(64, 10, 10))

# fitting the model with interaction (a + b + a:b)

model <- glm.nb(value ~ A*B, data=my.data)
anova(model, test="F")

     Df Deviance Resid. Df Resid. Dev      F Pr(>F)
NULL                    63     80.639
A     3    1.374        60     79.265 0.4581 0.7115
B     3    2.285        57     76.980 0.7616 0.5155
A:B   9    9.700        48     67.280 1.0778 0.3753

#until here it's ok, now I need to redistribute the 12 degrees of freedom (B+A:B -> 3+9) into 4 splitted factors (A within B1, A within B2...)

model2 <- glm.nb(value ~ A/((B=="Blevel1")+(B=="Blevel2")+(B=="Blevel3")+(B=="Blevel4")), data=my.data)
anova(model2, test="F")
                 Df Deviance Resid. Df Resid. Dev      F Pr(>F)
NULL                                63     80.639
A                 3    1.374        60     79.265 0.4581 0.7115
A:B == "Blevel1"  4    3.871        56     75.394 0.9676 0.4238
A:B == "Blevel2"  4    5.236        52     70.158 1.3090 0.2639
A:B == "Blevel3"  4    2.878        48     67.280 0.7195 0.5784
A:B == "Blevel4"  0    0.000        48     67.280

However, the 12 degrees of freedom are distributed as 4,4,4,0 and not 3,3,3,3, as I expected.
Is there a way of obtaining the split I need?

Thanks in advance, all the best!

Rafael.


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