Hello Chris, You may also use the R-package "calib".
Hugo On Tuesday 01 February 2011 17:08:13 Christopher Anderson wrote: > Hello, > > I am trying to fit my Elisa results (absorbance readings) to a standard > curve. To create the standard curve model, I performed a 4-parameter > logistic fit using the 'drc' package (ExpectedConc~Absorbance). This gave me > the following: > > FourP > > A 'drc' model. > > Call: > drm(formula = Response ~ Expected, data = SC, fct = LL.4()) > > Coefficients: > b:(Intercept) c:(Intercept) d:(Intercept) e:(Intercept) > 1.336 6.236 85.521 59.598 > > > summary(FourP) > > Model fitted: Log-logistic (ED50 as parameter) (4 parms) > > Parameter estimates: > > Estimate Std. Error t-value p-value > b:(Intercept) 1.33596 0.15861 8.42309 0.0011 > c:(Intercept) 6.23557 3.18629 1.95700 0.1220 > d:(Intercept) 85.52140 2.15565 39.67313 0.0000 > e:(Intercept) 59.59835 5.18781 11.48815 0.0003 > > Residual standard error: > > 1.866876 (4 degrees of freedom) > > Now that I have the 4 parameters, how do I fit the absorbance readings for > the analytical unknowns to the standard curve model (as to estimate the > concentrations of my unknown analytical samples)? > I can use the argument 'predict', but this predicts absorbance given > concentrations (y given x), I need to predict concentrations give absorbance > (x given y). > > Thanks! > Chris > > [[alternative HTML version deleted]] > > ______________________________________________ > 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.
