CONCURSO PROFESSOR ESTATISTICA (fwd)

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

---------- Forwarded message ----------
Date: Fri, 26 May 2006 10:40:34 -0300
From: Janilson Pinheiro de Assis <janilson@ufersa.edu.br>
To: Clarice G.B. Demetrio <clarice@carpa.ciagri.usp.br>
Subject: CONCURSO PROFESSOR ESTATISTICA



--PREZADA PROFESSORA CLARICE, SOLICITO A SENHORA A GENTILEZA DE DIVULGAR
SOBRE A ABERTURA DE CONCURSO PARA PROFESSOR DE ESTATÍSTICA(PERFIL MESTRADO
 EM QUALQUER ÁREA), NA UNIVERSIDADE FEDERAL RURAL DO SEMI-ÁRIDO EM MOSSORÓ
NO RIO GRANDE DO NORTE.

MAIORES INFORMAÇÕES ACESSAR HTTP://WWW.UFERSA.EDU.BR

ANTECIPADAMENTE AGRADEÇO A VALIOSA COLABORAÇÃO

ATENCIOSAMENTE

PROF.  JANILSON PINHEIRO

OBS.. OS ÚLTIMOS DOIS CONCURSOS REALIZADOS NÃO HOUVE INSCRITOS COM
DOUTORADO, E NÃO HOUVE APROVADOS A NÍVEL DE MESTRADO






>
> Applied Nonlinear Statistical Methods
> Thimothy OïBrien
>
> 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¦ ReuniÆo Anual da RegiÆo Brasileira da Sociedade Internacional de
> Biometria
> 24 a 26/05/2006, Botucatu, SP
> http://www.ibb.unesp.br/eventos/rbras/rbras_principal.php
> ---------------------------------------------------------------------
>