You need to combine all the data into one set and add another
variable, call it "dataset," with values 1 and 2. Then you can fit a
model to this **one combined" dataset that has an additive term for
"dataset," and, if you care to, test it for significance. However, as
usual, that probably will not be of much scientific value. I contend
that tests of significance mean little unless used in preplanned and
appropriately powered studies. Most statisticians would probably
characterize this contention as nuts, however, so feel free to ignore
it.
If you don't understand what I said, seek local counsel.
-- Bert
On Fri, Feb 24, 2012 at 11:28 PM, ?? <lm_mengxin at 163.com>
wrote:> Hi all:
>
> I have two curve models:
>
> model1<-nls(result ~ exp(b0 + b1*(time)), start = list(b0 = 0, b1 =
5),trace=TRUE,data=data1)
> model2<-nls(result ~ exp(b0 + b1*(time)), start = list(b0 = 0, b1 =
5),trace=TRUE,data=data2)
>
> I wanna compare the two models to find out whether the difference between
them is significant or not.
>
> How can I do then?
>
> Many thanks!
>
>
> My best
> ? ? ? ?[[alternative HTML version deleted]]
>
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--
Bert Gunter
Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm