[R] info

[Spencer Graves]

	  Calandra's dose-response function is very close to what you wrote: 
She has x = ln(z+1), while x = ln(z) and m = ln(gamma) would give what 
you wrote.  I would guess that your comments and references should help 
her.

Spencer Graves	

Paul, David A wrote:
> The most commonly used dose-response functions for nonlinear calibration 
> curves are the four- and five-parameter logistic functions.  The four-
> parameter logistic is specified as
> 
> F(z) = delta + (alpha - delta)/(1 + (z/gamma)^beta)
> 
> so I'm not sure where you are getting your dose-response functional form
> from.  In any case, you can fit this model using either nls( ) or nlme( ),
> depending on whether or not you want to fit a random-effects model.
> For references related to the four- and five-parameter logistic functions,
> you can read
> 
> 1.  Rodbard, D., and Frazier, G.R. (1975) "Statistical analysis of
> radioligand
> assay data," Methods Enzymol., vol. 37, p. 3 - 22.
> 
> 2.  Dudley, R.A., Edwards, P., and Ekins, R.P.  (1985)  "Guidelines for 
> immunoassay data processing," Clin. Chem., vol. 31, no. 8, p. 1264 - 1271
> 
> The first of these articles introduces the four-parameter logistic, and the
> second refines its parametrization as well as introduces the five-parameter
> logistic for use in situations where the calibration curve is asymmetric.
> You should also acquire "Mixed Effects Models in S and Splus", by Drs.
> Pinheiro and Bates if you intend to do anything with mixed effects models.
> 
> 
> Best,
>  
>  david paul
> 
> 
> 
> -----Original Message-----
> From: Andrea Calandra [mailto:a.CALANDRA at mclink.it] 
> Sent: Thursday, July 10, 2003 11:39 AM
> To: R-help at stat.math.ethz.ch
> Subject: [R] info
> 
> 
> HI
> 
> I'm a student in chemical engineering, and i have to implement an algoritm 
> about FIVE PARAMETERS INTERPOLATION for a calibration curve (dose, optical
> density)
> 
> y = a + (c - a) /(1+ e[-b(x-m])
> 
> where
> x = ln(analyte dose + 1)
> y = the optical absorbance data
> a = the curves top asymptote
> b = the slope of the curve
> c = the curves bottom asymptote
> m = the curve X intercept
> 
> Have you never seen this formula, because i don't fine information or 
> lecterature about solution of this!!!
> 
> Can i help me
> 
> Hi 
> Mr. Calandra
> 
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