[R-sig-ME] Zero-inflation with glmmadmb

[Pin chanratana]

Hi,

I have some question regarding to zero-inflation and hurdle model

- I fit a glmmadmb model of a species camera-trapped at waterholes during
the dry season. The data contain 51.9% of zeros and the
variance/mean=10.41. Following is a fit model and its result:

m1 <- glmmadmb(WS ~ depth + offset(log(TN)), ndata4, "nbinom1")

Coefficients:
            Estimate Std. Error z value Pr(>|z|)
(Intercept)   -3.677      0.214  -17.16   <2e-16 ***
depth          0.318      0.136    2.34     0.02 *

Negative binomial dispersion parameter: 6.6339 (std. err.: 1.7732)

- And then I check for overdispersion
E <- resid(m1, type= 'pearson')
N <- nrow(ndata4)
p <- length(coef(m1))
sum(E^2)/(N-p)  = 14.22

My questions are:
1. With the information above, should I go for more extend such as
zero-inflation and hurdle model?
2. To fit zero-inflation model, which approach is better way between
glmmadmb, zero-inflation and hurdle function?

Thanks,

	[[alternative HTML version deleted]]