[R] predictive logistic model cell-biology, non-dichotomous data

[Hugo Mildenberger]

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
> 
> 
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