This function computes confidence intervals for the estimated concentrations in a four-parameter logistic model fit to a set of dilution series in a reverse-phase protein array experiment.
getConfidenceInterval(result,
alpha=0.1,
nSim=50,
progmethod=NULL)An object of class RPPAFit, containing updated values for the
slots lower, upper, and conf.width that describe the
confidence interval.
object of class RPPAFit representing the
result of fitting a four-parameter logistic model
numeric scalar specifying desired significance of the confidence interval; the width of the resulting interval is 1 - alpha.
numeric scalar specifying number of times to resample the data in order to estimate the confidence intervals.
optional function that can be used to report progress.
Kevin R. Coombes coombes.3@osu.edu, P. Roebuck paul_roebuck@comcast.net, James M. Melott jmmelott@mdanderson.org
In order to compute the confidence intervals, the function assumes
that the errors in the observed \(Y\) intensities are independent
normal values, with mean centered on the estimated curve and
standard deviation that varies smoothly as a function of the (log)
concentration. The smooth function is estimated using
loess.
The residuals are resampled from this estimate and the model is refit;
the confidence intervals are computed empirically as symmetrically
defined quantiles of the refit parameter sets.
RPPAFit-class,
RPPAFit