\HeaderA{DNase}{Elisa assay of DNase}{DNase}
\keyword{datasets}{DNase}
\begin{Description}\relax
The \code{DNase} data frame has 176 rows and 3 columns of data
obtained during development of an ELISA assay for the recombinant
protein DNase in rat serum.
\end{Description}
\begin{Usage}
\begin{verbatim}DNase\end{verbatim}
\end{Usage}
\begin{Format}\relax
This data frame contains the following columns:
\describe{
\item[Run] an ordered factor with levels \code{10} < \dots < \code{3}
indicating the assay run.

\item[conc] a numeric vector giving the known concentration of the
protein. 

\item[density] a numeric vector giving the measured optical density
(dimensionless) in the assay.  Duplicate optical density
measurements were obtained. 

}
\end{Format}
\begin{Source}\relax
Davidian, M. and Giltinan, D. M. (1995) \emph{Nonlinear Models for
Repeated Measurement Data}, Chapman \& Hall (section 5.2.4, p. 134)

Pinheiro, J. C. and Bates, D. M. (2000) \emph{Mixed-effects Models in
S and S-PLUS}, Springer.
\end{Source}
\begin{Examples}
\begin{ExampleCode}
require(stats)
coplot(density ~ conc | Run, data = DNase,
    show = FALSE, type = "b")
coplot(density ~ log(conc) | Run, data = DNase,
    show = FALSE, type = "b")
## fit a representative run
fm1 <- nls(density ~ SSlogis( log(conc), Asym, xmid, scal ),
    data = DNase, subset = Run == 1)
## compare with a four-parameter logistic
fm2 <- nls(density ~ SSfpl( log(conc), A, B, xmid, scal ),
    data = DNase, subset = Run == 1)
summary(fm2)
anova(fm1, fm2)
\end{ExampleCode}
\end{Examples}

