%From Jose Pinheiro <jcp@rice.research.bell-labs.com>
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TITLE\\[2ex]
\Large Frank E Harrell Jr \\
\normalsize
Division of Biostatistics and Epidemiology \\
Department of Health Evaluation Sciences \\
University of Virginia School of Medicine \\
Box 800717 Charlottesville VA 22908 USA \\
{\tt fharrell@virginia.edu} \\
{\tt hesweb1.med.virginia.edu/biostat} \\
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\textsc{MEETING \\ DATE}
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\item ....
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\item ....
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\begin{slide*}
\Ti{Outline}
\begin{enumerate}
\item \rd{Introduction}
\begin{itemize}
\item motivating examples of \mg{linear} and \mg{non-linear}
mixed-effects models
\item $x^{2} - \sum_{i=1}^{n}\chi^{2}$
\item a sample of \splus commands for \mg{fitting} and
\mg{analyzing} mixed-effects models.
\end{itemize}
\item \rd{Grouped data}
\begin{itemize}
\item \spc \mg{repeated measures}, \mg{longitudinal} data, \mg{growth
curve} data
\item \spc \mg{multiply-nested} data
\item Data structures, \mg{classes}, and \mg{methods} for grouped
data in \splus
\item \spc \mg{Trellis} displays for grouped data
\end{itemize}
\end{enumerate}
\end{slide*}
\begin{slide*}
\Ti{Outline (cont.'d)}
\begin{enumerate}
\item[3.] \rd{Linear mixed-effects models}
\begin{itemize}
\item brief review of linear models
\item linear mixed-effects (\mg{LME}) model
\item \spc \mg{Multilevel} LME models
\item the \mg{lme} function in \splus
\end{itemize}
\item[4.] \rd{Extending the basic LME model}
\begin{itemize}
\item modelling the random effects \mg{covariance} structure
\item variance functions for modelling \mg{heteroscedasticity}
\item correlation structures: \mg{serial}, \mg{spatial}
\item S-PLUS capabilities for extending and customizing the
\mg{lme} function
\item the \mg{gls} function in \splus
\end{itemize}
\end{enumerate}
\end{slide*}
\begin{slide*}
\Ti{Outline (cont.'d)}
\begin{enumerate}
\item[5.] \rd{Nonlinear mixed-effects models}
\begin{itemize}
\item \spc \mg{nonlinear} regression model
\item starting estimates: \mg{self-starting} models
\item nonlinear mixed-effects (\mg{NLME}) models
\item the \mg{nlme} function in \splus
\item extending the basic \mg{NLME} model
\item using \mg{covariates} with \rd{nlme}
\end{itemize}
\end{enumerate}
\end{slide*}
\begin{slide*}
\Ti{Some examples}
{\red Orthodont} -- orthodontic growth data\\[2ex]
Distance (in millimeters) between the pituitary and the
pterygomaxillary fissure measured every two years for 27 children
(16 males, 11 females) from age 8 until age 14. Reported in
\cite{pot64roy}
{\tiny
\begin{verbatim}
distance age Subject Sex
1 26.0 8 M01 Male
2 25.0 10 M01 Male
3 29.0 12 M01 Male
4 31.0 14 M01 Male
5 21.5 8 M02 Male
6 22.5 10 M02 Male
. . .
104 19.5 14 F10 Female
105 24.5 8 F11 Female
106 25.0 10 F11 Female
107 28.0 12 F11 Female
108 28.0 14 F11 Female
\end{verbatim}}
\begin{itemize}
\item balanced data
\item linear growth with time
\fig{Photo_4}{This is a test. This is only a test.}
\item similar patterns across individuals, but with different
intercepts and slopes \cite{har98dev}
\end{itemize}
\end{slide*}
\bs
\small
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\bs{Abstract}
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. . . . .
}
\es
\end{document}