[R] GAM model with interactions between continuous variables and factors

[Joshua Wiley]

Yep that's exactly right! :)

On Mon, Mar 25, 2013 at 6:22 PM, Antonio P. Ramos
<ramos.grad.student at gmail.com> wrote:
> Just to clarify: I should include wealth - the categorical variable - as a
> fixed effects *and* within the smooth using the argument "by". It that
> correct? thanks a bunch
>
>
> On Mon, Mar 25, 2013 at 6:18 PM, Joshua Wiley <jwiley.psych at gmail.com>
> wrote:
>>
>> Hi Antonio,
>>
>> If wealth is a factor variable, you should include the main effect in
>> the model, as the smooths will be centered.
>>
>> Cheers,
>>
>> Josh
>>
>>
>>
>> On Mon, Mar 25, 2013 at 6:09 PM, Antonio P. Ramos
>> <ramos.grad.student at gmail.com> wrote:
>> > Hi all,
>> >
>> > I am not sure how to handle interactions with categorical predictors in
>> > the
>> > GAM models. For example what is the different between these bellow two
>> > models. Tests are indicating that they are different but their
>> > predictions
>> > are essentially the same.
>> >
>> > Thanks a bunch,
>> >
>> >> gam.1 <- gam(mortality.under.2~ maternal_age_c+ I(maternal_age_c^2)+
>> > +                s(birth_year,by=wealth) +
>> > +                + wealth + sex +
>> > +                residence+ maternal_educ + birth_order,
>> > +              ,data=rwanda2,family="binomial")
>> >>
>> >> gam.2 <- gam(mortality.under.2~ maternal_age_c+ I(maternal_age_c^2)+
>> > +                s(birth_year,by=wealth) +
>> > +                 + sex +
>> > +                residence+ maternal_educ + birth_order,
>> > +              ,data=rwanda2,family="binomial")
>> >>
>> >> anova(gam.1,gam.2,test="Chi")
>> > Analysis of Deviance Table
>> >
>> > Model 1: mortality.under.2 ~ maternal_age_c + I(maternal_age_c^2) +
>> > s(birth_year,
>> >     by = wealth) + +wealth + sex + residence + maternal_educ +
>> >     birth_order
>> > Model 2: mortality.under.2 ~ maternal_age_c + I(maternal_age_c^2) +
>> > s(birth_year,
>> >     by = wealth) + +sex + residence + maternal_educ + birth_order
>> >   Resid. Df Resid. Dev      Df Deviance  Pr(>Chi)
>> > 1     28986      24175
>> > 2     28989      24196 -3.6952  -21.378 0.0001938 ***
>> > ---
>> > Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>> >> str(rwanda2)
>> > 'data.frame': 29027 obs. of  18 variables:
>> >  $ CASEID            : Factor w/ 10718 levels "        1  5  2",..: 289
>> > 2243 7475 9982 6689 10137 7426 428 8415 10426 ...
>> >  $ mortality.under.2 : int  0 1 0 0 0 0 0 0 1 0 ...
>> >  $ maternal_age_disct: Factor w/ 3 levels "-25","+35","25-35": 1 1 1 1 1
>> > 1
>> > 3 1 3 1 ...
>> >  $ maternal_age      : int  18 21 21 23 21 22 26 18 27 21 ...
>> >  $ time              : int  3 3 3 3 3 3 3 3 3 3 ...
>> >  $ child_mortality   : num  0.232 0.232 0.232 0.232 0.232 ...
>> >  $ democracy         : Factor w/ 1 level "dictatorship": 1 1 1 1 1 1 1 1
>> > 1
>> > 1 ...
>> >  $ wealth            : Factor w/ 5 levels "Lowest quintile",..: 2 4 1 4
>> > 5 1
>> > 4 1 4 5 ...
>> >  $ birth_year        : int  1970 1970 1970 1970 1970 1970 1970 1970 1970
>> > 1970 ...
>> >  $ residence         : Factor w/ 2 levels "Rural","Urban": 1 1 1 1 2 1 1
>> > 1
>> > 1 2 ...
>> >  $ birth_order       : int  1 2 2 5 1 1 3 1 2 2 ...
>> >  $ maternal_educ     : Factor w/ 4 levels "Higher","No education",..: 3
>> > 2 2
>> > 3 4 2 3 2 2 2 ...
>> >  $ sex               : Factor w/ 2 levels "Female","Male": 1 1 2 2 1 1 2
>> > 2
>> > 2 2 ...
>> >  $ quinquennium      : Factor w/ 7 levels "00-5's","70-4",..: 2 2 2 2 2
>> > 2 2
>> > 2 2 2 ...
>> >  $ time.1            : int  3 3 3 3 3 3 3 3 3 3 ...
>> >  $ new_time          : int  0 0 0 0 0 0 0 0 0 0 ...
>> >  $ maternal_age_c    : num  -6.12 -3.12 -3.12 -1.12 -3.12 ...
>> >  $ birth_year_c      : num  -14.8 -14.8 -14.8 -14.8 -14.8 ...
>> >
>> >         [[alternative HTML version deleted]]
>> >
>> >
>> > ______________________________________________
>> > R-help at r-project.org mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-help
>> > PLEASE do read the posting guide
>> > http://www.R-project.org/posting-guide.html
>> > and provide commented, minimal, self-contained, reproducible code.
>> >
>>
>>
>>
>> --
>> Joshua Wiley
>> Ph.D. Student, Health Psychology
>> University of California, Los Angeles
>> http://joshuawiley.com/
>> Senior Analyst - Elkhart Group Ltd.
>> http://elkhartgroup.com
>
>



-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://joshuawiley.com/
Senior Analyst - Elkhart Group Ltd.
http://elkhartgroup.com