[R] Zero inflated negat. binomial model

Luciano La Sala lucianolasala at yahoo.com.ar
Thu Feb 4 21:26:39 CET 2010


Dear R crew: 

I think I am in the right mailing list. I have a very simple dataset consisting of two variables: cestode intensity and chick size (defined as CAPI). Intensity is clearly overdispersed, with way too many zeroes. I'm interested in looking at the association between these two variables, i.e. how well does chick size predict tape intensity?

I fit a zero inflated negat. binomial model using the "pscl" package. 

I built my model as follows and got the output below. 

> model <- zeroinfl(Int_Cesto ~ CAPI, dist = "negbin", EM = TRUE)
> model

Call:
zeroinfl(formula = Int_Cesto ~ CAPI, dist = "negbin", EM = TRUE)

Count model coefficients (negbin with log link):
(Intercept)         CAPI  
   -2.99182      0.06817  
Theta = 0.4528 

Zero-inflation model coefficients (binomial with logit link):
(Intercept)         CAPI  
    12.1364      -0.1572  

> summary(model)

Call:
zeroinfl(formula = Int_Cesto ~ CAPI, dist = "negbin", EM = TRUE)

Pearson residuals:
     Min       1Q   Median       3Q      Max 
-0.62751 -0.38842 -0.21303 -0.06899  7.29566 

Count model coefficients (negbin with log link):
            Estimate Std. Error z value Pr(>|z|)  
(Intercept) -2.99182    3.39555  -0.881   0.3783  
CAPI         0.06817    0.04098   1.664   0.0962 .
Log(theta)  -0.79222    0.45031  -1.759   0.0785 .

Zero-inflation model coefficients (binomial with logit link):
            Estimate Std. Error z value Pr(>|z|)   
(Intercept) 12.13636    3.71918   3.263  0.00110 **
CAPI        -0.15720    0.04989  -3.151  0.00163 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Theta = 0.4528 
Number of iterations in BFGS optimization: 1 
Log-likelihood: -140.2 on 5 Df
  
QUESTIONS

1. Is my model adequately specified?

2. CAPI is included in block 1 of output containing negative binomial regression coefficients the variable, and in block 2 corresponding to the inflation model. Does this make sense? If so...   

3. How should one interprete these results?

Thanks in advance!
LFLS      


      Yahoo! Cocina

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