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Overall model significance for poisson GLM
3 messages · Pat Wilkins, Bert Gunter, Ben Bolker
Not really an R question. Post on a statistics site like http://stats.stackexchange.com/ -- Bert
On Mon, Apr 9, 2012 at 9:51 AM, Pat Wilkins <pwilkin2 at illinois.edu> wrote:
Greetings, I am running glm models for species counts using a poisson link function. Normal summary functions for this provide summary statistics in the form of the deviance, AIC, and p-values for individual predictors. ?I would like to obtain the p-value for the overall model. ?So far, I have been using an analysis of deviance table to check a model against the null model with the intercept as the only predictor. Any advice on other methods to obtain the proper p-value would be appreciated. Thanks, Pat ? ? ? ?[[alternative HTML version deleted]]
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Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
Pat Wilkins <pwilkin2 <at> illinois.edu> writes:
Greetings, I am running glm models for species counts using a poisson link function. Normal summary functions for this provide summary statistics in the form of the deviance, AIC, and p-values for individual predictors. I would like to obtain the p-value for the overall model. So far, I have been using an analysis of deviance table to check a model against the null model with the intercept as the only predictor. Any advice on other methods to obtain the proper p-value would be appreciated.
What you're doing seems reasonable, although you can also dig the necessary values out of the summary and compute the p-value yourself: counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9) treatment <- gl(3,3) d.AD <- data.frame(treatment, outcome, counts) glm.D93 <- glm(counts ~ outcome + treatment, family=poisson(), data=d.AD) ## as you have been doing anova(update(glm.D93,.~1),glm.D93,test="Chisq") ## or sg1 <- summary(glm.D93) devdiff <- with(sg1,null.deviance-deviance) dfdiff <- with(sg1,df.null-df.residual) pchisq(abs(devdiff),df=dfdiff,lower.tail=FALSE)