From: Ghislain Vieilledent <ghislainv_at_gmail.com>

Date: Thu 28 Jul 2005 - 00:26:32 EST

Date: Thu 28 Jul 2005 - 00:26:32 EST

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I'm trying to use glm with factors:

> Pyr.1.glm<-glm(Pyrale~Trait,DataRav,family=poisson)

Then I test the significativity of Trait:

> anova(Pyr.1.glm,test="Chisq")

Analysis of Deviance Table

Terms added sequentially (first to last)

Df Deviance Resid. Df Resid. Dev P(>|Chi|)
**NULL 19 49.813
**

Trait 3 31.281 16 18.532 7.419e-07

Which means that variable Trait is significant for determining the value of P(Pyrale=k).

I tried to order the effects of the modalities of my variable Trait using:

Call:

glm(formula = Pyrale ~ Trait, family = poisson, data = DataRav)

Deviance Residuals:

Min 1Q Median 3Q Max

-1.7117 -0.8944 -0.6237 0.6390 1.5224

--- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 (Dispersion parameter for poisson family taken to be 1) Null deviance: 49.813 on 19 degrees of freedom Residual deviance: 18.532 on 16 degrees of freedom AIC: 61.85 Number of Fisher Scoring iterations: 5 ############################################################## I have therefore two questions: - Considering the values of estimated coefficients for Trait(i), does it mean that the bigger is the coefficient, the lower is the probability considering the mathematical expression (exp(-m))? - How can I check that coefficients are significatively different one from each other (as with function TukeyHSD for other models)? Thanks for you help. Regards Ghislain. -- Ghislain Vieilledent 30, rue Bernard Ortet 31 500 TOULOUSE 06 24 62 65 07 [[alternative HTML version deleted]] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.htmlReceived on Thu Jul 28 00:35:18 2005

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