Dear all,

I am new to R and my question may be trivial to you...
I am doing a GLM with binomial errors to compare proportions of species in
different categories of seed sizes (4 categories) between 2 sites.
 In the model summary the residual deviance is much higher than the degree
of freedom (Residual deviance: 153.74  on 4  degrees of freedom) and even
after correcting for overdispersion by using a quasibinomial error structure
instead of binomial the residual deviance does not change. Is this a data
problem and I cannot use this statistic or is it because I do something
wrong with R (see models attached)?

Thanks a lot for your help!
Anna


first model with binomial error structure:

> success<-c(14,43,44,1,13,28,56,8)
> failure<-c(88,59,58,101,92,77,49,97)
> "fragment"<-c(1,1,1,1,2,2,2,2)
> "type"<-c(1,2,3,4,1,2,3,4)
> y<-cbind(success,failure)
> model<-glm(y~fragment*type,binomial)
> summary(model)
Call:
glm(formula = y ~ fragment * type, family = binomial)

Deviance Residuals:
      1        2        3        4        5        6        7        8
-4.0175   3.3716   4.5052  -6.0071  -2.8063   0.5449   6.0414  -5.0184

Coefficients:
              Estimate Std. Error z value Pr(>|z|)
(Intercept)    0.04433    0.61072   0.073   0.9421
fragment      -0.65477    0.39001  -1.679   0.0932 .
type          -0.46664    0.23027  -2.027   0.0427 *
fragment:type  0.26636    0.14455   1.843   0.0654 .
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 157.96  on 7  degrees of freedom
Residual deviance: 153.74  on 4  degrees of freedom
AIC: 196.31

Number of Fisher Scoring iterations: 5

second model with quasibinomial error structure:
> summary(model2)

Call:
glm(formula = y ~ fragment * type, family = quasibinomial)

Deviance Residuals:
      1        2        3        4        5        6        7        8
-4.0175   3.3716   4.5052  -6.0071  -2.8063   0.5449   6.0414  -5.0184

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)    0.04433    3.63550   0.012    0.991
fragment      -0.65477    2.32169  -0.282    0.792
type          -0.46664    1.37073  -0.340    0.751
fragment:type  0.26636    0.86048   0.310    0.772

(Dispersion parameter for quasibinomial family taken to be 35.43628)

    Null deviance: 157.96  on 7  degrees of freedom
Residual deviance: 153.74  on 4  degrees of freedom
AIC: NA

Number of Fisher Scoring iterations: 5

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