[R] A question about using “by” in GAM model fitting of interaction between smooth terms and factor

[willow1980]

Dear Simon,
Thank you so much!
Actually, it seems that Crawley's R book adopted the information from that
earlier version and he discussed "by" in the context of that version. 
I will take a practice according to your suggestion.
Thanks again!
Jianghua


Simon Wood-4 wrote:
> 
> The problem here is that the help page you are looking at appears to be
> from 
> an earlier version of `mgcv' than you are using (it's from a version that
> did 
> not support factor `by' variables). Take a look at ?gam.models for the 
> version that you are actually using. 
> 
> The reason that your models give the same fit is because ~z and ~z-1
> differ 
> only in the identifiability constraints used, when `z' is a factor (for
> all 
> linear type models). 
> 
> As far as model reasonableness is concerned: it's a bit difficult to say 
> without knowing the context. The only thing that stands out is that you
> are 
> using an isotropic `s' term for the interaction --- this is fine if
> `byear' 
> and `FAFR' are really naturally on the same scale, but if not tensor
> product 
> smooths (`te') may be preferable, as the are independent of the relative 
> scaling of the variables. For plot interpretability, I'd drop the `main 
> effect' smooths and just leave in the interaction.  
> 
> best,
> Simon 
> 
> On Tuesday 05 May 2009 16:53, willow1980 wrote:
>> I am a little bit confusing about the following help message on how to
>> fit
>> a GAM model with interaction between factor and smooth terms from
>> http://rss.acs.unt.edu/Rdoc/library/mgcv/html/gam.models.html:
>> “Sometimes models of the form:
>> E(y)=b0+f(x)z
>> need to be estimated (where f is a smooth function, as usual.) The
>> appropriate formula is:
>> y~z+s(x,by=z)
>> - the by argument ensures that the smooth function gets multiplied by
>> covariate z, but GAM smooths are centred (average value zero), so the z+
>> term is needed as well (f is being represented by a constant plus a
>> centred
>> smooth). If we'd wanted:
>> E(y)=f(x)z
>> then the appropriate formula would be: y~z+s(x,by=z)-1.”
>> When I tried two scripts, I found they gave the same results. That is,
>> the
>> codes “y~z+s(x,by=z)” and “y~z+s(x,by=z)-1” gave the same results. The
>> following is my result:
>> ###########################################################################
>> “anova(model1,model2,test="Chisq")
>> Analysis of Deviance Table
>>
>> Model 1: FLBS ~ SES + s(FAFR, by = SES) + s(byear, by = SES) + s(FAFR,
>>     byear, by = SES)
>> Model 2: FLBS ~ SES + s(FAFR, by = SES) + s(byear, by = SES) + s(FAFR,
>>     byear, by = SES) - 1
>>    Resid. Df Resid. Dev         Df  Deviance P(>|Chi|)
>> 1 1.2076e+03     1458.4
>> 2 1.2076e+03     1458.4 1.9099e-11 5.030e-10 2.074e-10”
>> ###########################################################################
>> Is this in conflict with above statement that “If we'd wanted: E(y)=f(x)z
>> then the appropriate formula would be: y~z+s(x,by=z)-1.”? Also, if you
>> are
>> familiar with GAM modelling, please have a look at my modelling process.
>> That is, I want to study how one factor together with two smooth terms
>> will
>> influence the response. In model2, I also fitted the interaction between
>> two smooth terms, together with the interaction of this interaction with
>> factor. Is model 2 reasonable? I find it is rather complicated to
>> interpret
>> the plot of model 2.
>> Thank you very much for helping!
> 
> -- 
>> Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK
>> +44 1225 386603  www.maths.bath.ac.uk/~sw283 
> 
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