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.stud...@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@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 ______________________________________________ R-help@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.
