[R] logistic regression

[Heike Zimmermann]

Hello,

I have a problem concerning logistic regressions.  When I add a quadratic
term to my linear model, I cannot draw the line through my scatterplot
anymore, which is no problem without the quadratic term.
In this example my binary response variable is "incidence", the explanatory
variable is "sun":
> model0<-glm(incidence~1,binomial)
> model1<-glm(incidence~sun,binomial)
> anova(model0,model1,test="Chi")
Analysis of Deviance Table

Model 1: incidence ~ 1
Model 2: incidence ~ sun
  Resid. Df Resid. Dev  Df Deviance P(>|Chi|)
1       299     332.94                       
2       298     287.19   1    45.74 1.349e-11
> qsun<-sun^2
> model2<-glm(incidence~sun+qsun,binomial)
> anova(model1,model2,test="Chi")
Analysis of Deviance Table

Model 1: incidence ~ sun
Model 2: incidence ~ sun + qsun
  Resid. Df Resid. Dev  Df Deviance P(>|Chi|)
1       298    287.194                       
2       297    280.623   1    6.571     0.010

So the second, non-linear, model explains more than the first. 
Now to create a graph I write:

> plot(sun,incidence)
> min(sun)
[1] 0
> max(sun)
[1] 90
> xsun<-seq(0,90,1)

>lines(xsun,predict(model2,type="response",data.frame(sun=xsun)))

Error in model.frame(formula, rownames, variables, varnames, extras,
extranames,  : 
        variable lengths differ
> 

So this is the message I receive everytime I try to draw the fitted values
of my model. I know for sure that exactly the same command works in S-Plus
(with the same data). How is ist possible to do this in R?

Thank you in advance, Heike

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