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
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Etienne Toffin, PhD Student
Unit of Social Ecology
Université Libre de Bruxelles, CP 231
Boulevard du Triomphe
B-1050 Brussels
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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