Andreas, the jpg files you linked below do not exist, but if all you need for the moment is a predictive model and graphical displays of the fitted model and the calibrated sample data, then the R - package "calib" will do it very well. Usage is very simple.
Best, Hugo On Tuesday 14 June 2011 00:11:37 andreasss wrote: > Hi everyone, > > I would like to fit a predictive model to my data in order to compare > absorbance readings to a toxin standard. This data was obtained by exposing > red blood cells to different toxin concentrations, which lead to the lysis > of the red blood cells, increasing the absorbance (hemoglobin is freed). The > data has a sigmoid shape (see below), so I thought about fitting a logistic > model to the data so that I will be able to determine the toxin equivalent > of new absorbance readings. > http://r.789695.n4.nabble.com/file/n3595812/Unbenannt.jpg > > The data points for this curve are: > http://r.789695.n4.nabble.com/file/n3595812/qweqwe.jpg > I must admit that I am totally lost. I have done a fair bit of reading on > logistic regression, but most seem to focus on binary outcomes or > multinomial analysis. Do I have to somehow assign 'pass' or 'fail' to this > data, maybe 0 and 100% lysis? Or is the logistic model not suitable for what > I am planning. All I want to do is to fit a predictive model to this data > and to graphically represent the 'best fit'. Any help will be greatly > appreciated. > > Thanks in advance, > > Andreas > > > -- > View this message in context: > http://r.789695.n4.nabble.com/predictive-logistic-model-cell-biology-non-dichotomous-data-tp3595812p3595812.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. ______________________________________________ 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.