Spencer,

Le 22-avr.-09 à 03:33, spencerg a écrit :

Is your first model a special case of the second with eta1 = 0? If yes, what about using 2*log(likelihood ratio) being approximately chi-square?
Yes, the first model is a special case of the second with eta1=0…
Could you give me more explanation about this method with likelihood ratio and chi-square ?

Can you recast the problem to use "nls"? If yes, might the 'nls' methods for 'anova' or 'profile' give you what you want?

I tried fitting the distribution using nls (perfect fitting). However, if I well understand 'anova' is used here to test alternative fittings (of alternative models) on a same distribution. Here I want to test the difference of parameter values between two different distributions and one same model
 (i.e. I want to test if eta1(TREATMENT) is different

Do you have any other idea ?

Thanks,

Etienne

One short question about nls: are there any reason why nlm should be used rather than nls and vice-versa (nls results are quite more full than those of nlm)?



    Hope this helps,
    Spencer

Etienne Toffin wrote:
Hi,

I'm using a non linear model to fit experimental survival curves.

This model describes the fraction of "still active" experiments as a function of time t as follows:
f(t)=(1+exp(-etaD*cD)) / (1+exp(etaD(t-cD)))

Moreover, when experiments are still active, they may change of state (from 0 to 1). But they may fall inactive before changing their state (their state still equals 0). The survival curve of state may also be fitted with the following model: f(A)=(1+exp(-eta1*c1)) / (1+exp(eta1(t-c1))) * (1+exp(-etaD*cD)) / (1+exp(etaD(t-cD)))

I estimate with nlm 1°) values of etaD and cD parameters and 2°) inject them as constant in the function to be minimized by nlm to estimate values of eta1 and c1.

I perform these estimations for two different experimental conditions that both have their values of etaD,eta1, cD and c1.

I would like to know if there is any statistical method to compare the estimated values of parameters of the two distributions ? And wether it's the case, how to perform it in R ?

Hope I'm clear enough for getting help,

Etienne

-------------------------------------------------------------------
Etienne Toffin, PhD Student
Unit of Social Ecology
Université Libre de Bruxelles, CP 231
Boulevard du Triomphe
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Belgium

Tel: +32(0)2/650.55.30
Fax: +32(0)2/650.57.67
http://www.ulb.ac.be/sciences/use/toffin.html

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