[R] degrees of freedom question
bates at stat.wisc.edu
Thu Aug 23 15:36:37 CEST 2007
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an out-of-date version of R and lack of R code to be more than a
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