Minicurso Applied Nonlinear Statistical Methods

["Clarice G.B. Demetrio" <clarice@carpa.ciagri.usp.br>]

Titulo: Applied Nonlinear Statistical Methods
Professor: Timothy OďBrien (Department of Mathematics and Statistics,
Loyola University Chicago, USA)
Data: 30/06/2005
Local: Depto de Ciencias Exatas, ESALQ/USP
Horario: das 8 as 12h e das 14 as 18h

Applied Nonlinear Statistical Methods
Thimothy OďBrien

Researchers often recognize that nonlinear regression models are more
applicable for modelling their physical and medical processes than are
linear ones for several important reasons.  Nonlinear models usually fit
their data well and often in a more parsimonious manner (typically with
far fewer model parameters).  Also, nonlinear models and the corresponding
model parameters are usually more scientifically meaningful.  But
selecting an efficient experimental design; choosing, fitting and
interpreting an appropriate nonlinear model; and deriving and interpreting
confidence intervals for key model parameters can present practitioners
with fundamental and important challenges.

This course first reviews the essentials of linear regression, and
subsequently introduces and illustrates generalized linear models (such as
logistic regression), Gaussian nonlinear models, and generalized nonlinear
models, focusing on applications.  Illustrations are given from the
domains of bioassay, relative potency and drug or similar compound synergy
useful in biomedical and environmental sciences.  Caveats are discussed
regarding convergence, diagnostics, and the inadequacy of standard (Wald)
confidence intervals  which are the intervals provided by most software
packages.  Extensions to bivariate situations (such as those focusing on
both efficacy and safety of drugs) and censored (survival) analysis are
also provided, as are implications for experimental design.
Implementation using the SAS© statistical software package will be
discussed, but references will be made to other packages as well.


Course Outline

I.	Brief review of simple and multiple linear regression; two-sample
t-tests, ANOVA, ANOCOV (analysis of covariance); diagnostics and model
checking; logistic regression.
II.	Introduction to Gaussian nonlinear models; practical concerns
(choosing a model, starting values); nonlinear contrasted with linear
models and with generalized linear models; applications (substance
dissolution and enzyme kinetics); confidence regions, intervals, and the
impact of curvature (nonlinearity, asymmetry).
III.	Diagnostics and model checking; examples involving ELISAs (and
other assays) and pharmacokinetics; extensions of classical methods
including modelling variance functions and correlated responses; brief
discussion of mixed and hierarchical nonlinear models.
IV.	Generalized nonlinear models and applications in bioassay,
relative potency, and drug/similar compound synergy modelling; usefulness
and limitations of the IML and NLMixed SAS© procedures.
V.	Experimental design strategies including benefits and limitations
of optimal designs; robust optimal design strategies; geometric designs.
VI.	Extensions to bivariate Gaussian and binomial responses and to
censored data in the context of the detection of drug/similar compound
synergy.

Timothy E. OBrien, Ph.D.

Dr. Timothy E. OBrien is a tenured associate professor with the graduate
faculty in the Department of Mathematics and Statistics, Loyola University
of Chicago.  Dr. OBrien received his Ph.D. in Statistics from North
Carolina State University in 1993.  His dissertation topic, New Design
Strategies for Parameter Estimation and Model Discrimination in Nonlinear
Regression Models focuses on optimal experimental design, generalized
linear and nonlinear modeling, and computer intensive methods, with
applications to drug synergy research.  Dr. OBrien also received an M.A.
in Statistics from the University of Rochester (1987), an M.A. in
Mathematics from Syracuse University (1985), and a B.A. in Mathematics and
Economics from Pace University (1978).  He is a member of ASA, ENAR, IASC,
IASE, and ISI.

Dr. OBrien has made several contributions to the theory and methods of
optimal experimental design, particularly regarding nonlinear modeling.
Some of his publications appear (or will appear) in Biometrika, Statistica
Sinica, Journal of Statistical Planning and Inference, The American
Statistician, Journal of Agricultural, Biological, and Environmental
Statistics, the Journal of Chemical Ecology, Computational Statistics and
Data Analysis, and the Journal of Data Science.  Dr. OBrien also published
three book chapters on optimal design, robust design, and lack of fit, for
nonlinear regression models, as well as several refereed conference
proceedings (e.g., Proceedings of the 15th Conference on Applied
Statistics in Agriculture, Proceedings of Agro-Industrie et Methodes
Statistiques) and collaborative papers in refereed biomedical journals
(e.g., Development, Annals of Neurology, Cell and Tissue Research), which
illustrate the immediate application of his theoretical work.  Dr. OBrien
has served numerous times as a referee for top tier statistical journals,
and he is frequently invited to both domestic and international
conferences and universities to speak on his theoretical developments and
their applications to pharmacology and pharmacokinetics.  Dr. OBrien won a
SUGI Best Contributed Paper Award for demonstrating how some of his
metholdogical work on optimal designs for nonlinear regression models can
be implemented with SAS©

Dr. OBrien's previous industrial and academic work experience contributed
greatly to both the direction and applications targeted for his current
research activities.  For example, Dr. OBrien spent two years as a
biostatistical consultant at Janssen Pharmaceutics NV, two years as an
internal statistical consultant and biostatistician at Novartis Pharma AG,
and three years as an assistant statistician at Glaxo. In addition, Dr.
OBrien also provided statistical consulting services to SmithKline,
Bristol Myers Squibb, Chiron, and Amgen.  Dr. OBriens previous domestic
academic experience includes Assistant Professor positions at Loyola
University of Chicago, the University of Georgia, and Washington State
University.  Internationally, Dr. OBrien has been a Visiting Professor at
both Limburgs Universitair Centrum (Belgium) and Katholieke Universiteit
Leuven (Belgium), a Visiting Lecturer at the University of Natal at
Pietermaritzburg (South Africa), and he was awarded two postdoctoral
fellowships, one at the Universit„t Augsburg (Germany) and the other at
INRA, Laboratorie de Biometrie (France).

Dr. OBrien has a strong interest in and committment to statistical and
mathematical education.  He has developed and taught a wide range of
theoretical and applied statistics, statistical computing, statistical
programming, statistical consulting, and mathematics courses, at both the
graduate and undergraduate levels, at both domestic and universities
abroad.  In addition, Dr. OBrien has taken the time to supervise more than
a dozen directed reading courses with graduate students in nonlinear mixed
modeling, generalized linear models, nonlinear regression, differential
geometry, optimal design, multivariate statistics, survival analysis,
advanced statistical inference, and drug synergy, some of which led to the
students dissertation research.  Dr. OBrien has been invited to
conferences on teaching statistics and also to universities to share his
ideas on successful teaching, and he has recently written an invited book
chapter on Innovatice Methods in Undergraduate Courses Following Calculus
which is to appear in the MAA Notes series.  Perhaps the clearest
demonstration of Dr. OBriens commitment to education was his two-year tour
with the Peace Corps in French West Africa where he taught several
mathematics courses preparing lyc‚e students for the French Boccaleureate
exam and entrance into university.




  Clarice
---------------------------------------------------------------------
Clarice Garcia Borges Demetrio
Departamento de Ciencias Exatas      | Phone: +55 019 34294144 R:216
ESALQ/USP                            | Fax:   +55 019 34294346
Caixa Postal 9                       | http://ce.esalq.usp.br/
13418-900 PIRACICABA, SP             |
BRASIL                               | clarice@carpa.ciagri.usp.br

--------------------------------------------------------------------
51¦ ReuniĆo Anual da RegiĆo Brasileira da Sociedade Internacional de
Biometria
24 a 26/05/2006, Botucatu, SP
http://www.ibb.unesp.br/eventos/rbras/rbras_principal.php
---------------------------------------------------------------------