[R] interpreting interactions in a model

[Greg Snow]

The Predict.Plot function in the TeachingDemos package can help you visualize interactions.  It will work best if Month is treated as a continuous variable.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of gaiarrido
> Sent: Wednesday, August 17, 2011 2:57 AM
> To: r-help at r-project.org
> Subject: [R] interpreting interactions in a model
> 
> Hi,
> I´ve got this model
> > model<-glm(prevalence~agesex+agesex:month,binomial)
> 
> and the output of anova is like that
> 
> > anova(model,test="Chisq")
>                           Df Deviance Resid. Df Resid. Dev P(>|Chi|)
> NULL                            524     206.97
> agesex                 2   9.9165       522     197.05  0.007025 **
> agesex:month        9  18.0899       513     178.96  0.034145 *
> 
> I don´t know how to interpret the interaction "agesex:month", my mind
> doubt
> between 2 options:
> a) For a giving group of "agesex" there are differences between months
> b)There are differences between groups of "agesex" in some months but
> not in
> others.
> 
> Which option is correct?
> Thanks very much
> 
> -----
> Mario Garrido Escudero
> PhD student
> Dpto. de Biología Animal, Ecología, Parasitología, Edafología y Qca.
> Agrícola
> Universidad de Salamanca
> --
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