Re: [R] interpreting interactions in a model

2011-08-23 Thread 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.s...@imail.org
801.408.8111


 -Original Message-
 From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
 project.org] On Behalf Of gaiarrido
 Sent: Wednesday, August 17, 2011 2:57 AM
 To: r-help@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|)
 NULL524 206.97
 agesex 2   9.9165   522 197.05  0.007025 **
 agesex:month9  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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Re: [R] interpreting interactions in a model

2011-08-18 Thread gaiarrido
Thanks,
 I´ve found the differencies with a posteriori tests.
I don't put the term month because it is not significant.

-
Mario Garrido Escudero
PhD student
Dpto. de Biología Animal, Ecología, Parasitología, Edafología y Qca. Agrícola
Universidad de Salamanca
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Re: [R] interpreting interactions in a model

2011-08-17 Thread Dennis Murphy
Hi:

On Wed, Aug 17, 2011 at 1:56 AM, gaiarrido gaiarr...@usal.es wrote:
 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 *

Where is the month main effect? Even if it's 'not significant', it
belongs in the model (principle of marginality).

 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?

In the absence of a reproducible example, no one can say, but it's
within the realm of possibility that either or both could be correct.
The significance test for interaction indicates *whether* an
interaction effect exists - it doesn't tell you *what type* of
interaction exists. Conditional on the inference that an interaction
effect is present, the next step of the analysis is to investigate the
nature of the interaction. This could involve planned contrasts,
multiple comparisons, graphics, etc. The car, effects, multcomp and HH
packages can be useful for these types of investigations.

HTH,
Dennis

 Thanks very much

 -
 Mario Garrido Escudero
 PhD student
 Dpto. de Biología Animal, Ecología, Parasitología, Edafología y Qca. Agrícola
 Universidad de Salamanca
 --
 View this message in context: 
 http://r.789695.n4.nabble.com/interpreting-interactions-in-a-model-tp3749430p3749430.html
 Sent from the R help mailing list archive at Nabble.com.

 __
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 https://stat.ethz.ch/mailman/listinfo/r-help
 PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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