On Fri, Apr 10 2009, Peter Graff wrote: > I was wondering if someone knew how to get a glm (family=poisson) to > spit out the Model Likelihood ratio, or more generally how to > calculate it from the deviance.
Likelihood ratios apply between to different models, single models have
a log likelihood. Are you comparing two models?
To get the log likelihood for a single model, you can use logLik(model).
To do a likelihood ratio test between two models, you can use
anova(model1, model2).
Using the example from ?glm,
--8<---------------cut here---------------start------------->8---
## EXAMPLE
## Dobson (1990) Page 93: Randomized Controlled Trial :
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
print(d.AD <- data.frame(treatment, outcome, counts))
glm.D93 <- glm(counts ~ outcome + treatment, family=poisson())
anova(glm.D93)
summary(glm.D93)
## LOG LIKELIHOOD
logLik(glm.D93)
## MODEL COMPARISON
glm.D93.1 <- glm(counts ~ 1, family=poisson())
anova(glm.D93, glm.D93.1)
--8<---------------cut here---------------end--------------->8---
HTH,
/au
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Austin Frank
http://aufrank.net
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