[R] degrees of freedom question

[Douglas Bates]

On 8/22/07, Greg Tarpinian <sasprog474 at yahoo.com> wrote:
>     R2.3, WinXP

> Dear all,

> I am using the following functions:

>  f1 = Phi1+(Phi2-Phi1)/(1+exp((log(Phi3)-log(x))/exp(log(Phi4)))
>  f2 = Phi1+(Phi2-Phi1)/(1+exp((log(Phi3)-log(r)-log(x))/exp(log(Phi4)))

> subject to the residual weighting

>  Var(e[i]) = sigma^2 * abs( E(y) )^(2*Delta)

> Here is my question, in steps:

>  1.  Function f1 is separately fitted to two different datasets
>      corresponding to two different dose response curves.  These
>      fits are unweighted.
>  2.  Function f2 is fitted to the pooled data such that the two
>      dose response curves are assumed to differ _only_ in log(r).
>      This fit is also unweighted.
>  3.  The residuals from #2 are used to estimate an appropriate
>      sigma^2 and Delta to use in weighting.
>  4.  The functions described in #1 and #2 are refitted, but this
>      time weighted using the information gathered in #3.
>  5.  How many degrees of freedom should be allocated to the
>      weighted residual sums of squares?  (There are three such
>      SSE's, one for each individual model, and one for the overall
>      joint model)

Which R function(s) are you using to fit these models?  Did you try a
call to anova with multiple arguments?

(Or should we consider your email address of "sasprog474", mention of
an out-of-date version of R and lack of R code to be more than a
coincidence?)