I would suggest a model with a baseline level, something like

nls(AMP~E0+(Emax-E0)*Time**gamma/(EC50**gamma+Time**gamma),data=your data,
start=list(EC50=50,gamma=2,E0=0.2,Emax=1.2))->mod.test

AIC(mod.test) does improve. Hope this helps.

Jun

On Wed, Aug 19, 2009 at 5:04 AM, Dani Valverde <daniel.valverde@uab.cat>wrote:

> Hello,
> I have this data:
>  Time  AMP
>     0 0.2000000
>    10 0.1958350
>    20 0.2914560
>    40 0.6763628
>    60 0.8494534
>    90 0.9874526
>   120 1.0477692
>
> where AMP is the concentration of this metabolite with time. If you plot
> the data, you can see that it could be fitted using a logistic
> regression. For this purpose, I used this code:
>
> AMP.nls <- nls(AMP~SSlogis(Time,Asym, xmid, scal), data =
> concentrations,model=T)
>
> When plotting the fitted function, it seems that it fits quite well at
> the end of the time. However, at the beginning it seems that the fit is
> not so good. How can I achieve a better fit? Forgive me if it is a
> stupid question, but I am just starting with non linear regression.
> Thank you,
>
> Dani
> --
> [?]
>
> ______________________________________________
> 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.
>



-- 
Jun Shen PhD
PK/PD Scientist
BioPharma Services
Millipore Corporation
15 Research Park Dr.
St Charles, MO 63304
Direct: 636-720-1589

	[[alternative HTML version deleted]]


