Hi,
I am trying to find out how to interpret the summary output from a neg
bin GLM?
I have 3 significant variables and I can see whether they have a
positive or negative effect, but I can't work out how to calculate the
magnitude of the effect on the mean of the dependent variable. I used
a log link function so I think I might have to use the antilogs of the
coefficients but I have no idea how this relates to the dependent
variable??
Any help would be much appreciated.
My model and output is shown below.
Thanks
Anna
Call:
glm.nb(formula = Pass ~ Dist + Time + Wind, data = bats, link = "log",
init.theta = 0.8510838809)
Deviance Residuals:
Min 1Q Median 3Q Max
-2.2784 -0.9967 -0.3594 0.2603 2.2142
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.3329718 0.3603909 9.248 < 2e-16 ***
Dist 0.0008892 0.0002377 3.741 0.000183 ***
Time -0.0159068 0.0034665 -4.589 4.46e-06 ***
Wind -0.1177475 0.0346301 -3.400 0.000673 ***
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
(Dispersion parameter for Negative Binomial(0.8511) family taken to be 1)
Null deviance: 134.586 on 79 degrees of freedom
Residual deviance: 92.725 on 76 degrees of freedom
AIC: 501.21
Number of Fisher Scoring iterations: 1
Theta: 0.851
Std. Err.: 0.164
2 x log-likelihood: -491.211
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