R help - Mar 2016 - How to solve an NLME problem?

I have a nonlinear model where I want to include random coefficients for a
sample of random SUBJECTS. The fixed effects part of the model is Y ~ B + (T -
B) / (1 + 10**(X - C)) and I would like to include random coefficients b for B,
t for T, and c for C. The model is a fairly well-known three-parameter
log-inhibitor model where Y is a measure of growth at X = log(CONCENTRATION), B
is the unknown lower asymptote, T is the unknown upper asymptote, and C is the
unknown log(IC50), where IC50 is the half maximal inhibitory concentration. I do
not know how to solve this problem in R, where I am assuming NLME contains the
appropriate methodology.

	[[alternative HTML version deleted]]

David C Blouin <dblouin <at> lsu.edu> writes:
>  I have a nonlinear model where I want to include random
> coefficients for a sample of random SUBJECTS. The fixed effects part
> of the model is Y ~ B + (T - B) / (1 + 10**(X - C)) and I would like
> to include random coefficients b for B, t for T, and c for C. The
> model is a fairly well-known three-parameter log-inhibitor model
> where Y is a measure of growth at X = log(CONCENTRATION), B is the
> unknown lower asymptote, T is the unknown upper asymptote, and C is
> the unknown log(IC50), where IC50 is the half maximal inhibitory
> concentration. I do not know how to solve this problem in R, where I
> am assuming NLME contains the appropriate methodology.
> [[alternative HTML version deleted]]
  something like

  nlme(Y ~ B + (T - B) / (1 + 10**(X - C)),
       random=B+T+C~group,
       data=your_data,
       start=list(fixed=c(B=something,T=something2,C=something3)))

 Follow-ups to r-sig-mixed-models at r-project.org, please ...