\HeaderA{Theoph}{Pharmacokinetics of theophylline}{Theoph}
\keyword{datasets}{Theoph}
\begin{Description}\relax
The \code{Theoph} data frame has 132 rows and 5 columns of data from
an experiment on the pharmacokinetics of theophylline.
\end{Description}
\begin{Usage}
\begin{verbatim}Theoph\end{verbatim}
\end{Usage}
\begin{Format}\relax
This data frame contains the following columns:
\describe{
\item[Subject] an ordered factor with levels \code{1}, \dots, \code{12}
identifying the subject on whom the observation was made.  The
ordering is by increasing maximum concentration of theophylline
observed.

\item[Wt] weight of the subject (kg).

\item[Dose] dose of theophylline administered orally to the subject (mg/kg).

\item[Time] time since drug administration when the sample was drawn (hr).

\item[conc] theophylline concentration in the sample (mg/L).

}
\end{Format}
\begin{Details}\relax
Boeckmann, Sheiner and Beal (1994) report data from a study by
Dr. Robert Upton of the kinetics of the anti-asthmatic drug
theophylline.  Twelve subjects were given oral doses of theophylline
then serum concentrations were measured at 11 time points over the
next 25 hours.

These data are analyzed in Davidian and Giltinan (1995) and Pinheiro
and Bates (2000) using a two-compartment open pharmacokinetic model,
for which a self-starting model function, \code{SSfol}, is available.
\end{Details}
\begin{Source}\relax
Boeckmann, A. J., Sheiner, L. B. and Beal, S. L. (1994), \emph{NONMEM
Users Guide: Part V}, NONMEM Project Group, University of
California, San Francisco.

Davidian, M. and Giltinan, D. M. (1995) \emph{Nonlinear Models for
Repeated Measurement Data}, Chapman \& Hall (section 5.5, p. 145 and
section 6.6, p. 176)

Pinheiro, J. C. and Bates, D. M. (2000) \emph{Mixed-effects Models in
S and S-PLUS}, Springer (Appendix A.29)
\end{Source}
\begin{SeeAlso}\relax
\code{\LinkA{SSfol}{SSfol}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
require(stats); require(graphics)
coplot(conc ~ Time | Subject, data = Theoph, show.given = FALSE)
Theoph.4 <- subset(Theoph, Subject == 4)
fm1 <- nls(conc ~ SSfol(Dose, Time, lKe, lKa, lCl),
           data = Theoph.4)
summary(fm1)
plot(conc ~ Time, data = Theoph.4,
     xlab = "Time since drug administration (hr)",
     ylab = "Theophylline concentration (mg/L)",
     main = "Observed concentrations and fitted model",
     sub  = "Theophylline data - Subject 4 only",
     las = 1, col = 4)
xvals <- seq(0, par("usr")[2], len = 55)
lines(xvals, predict(fm1, newdata = list(Time = xvals)),
      col = 4)
\end{ExampleCode}
\end{Examples}

