[ABE-L] Fwd: IV WORKSHOP ON "LONGITUDINAL AND INCOMPLETE DATA"

Sex Nov 9 17:07:29 -03 2018

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IV WORKSHOP ON "LONGITUDINAL AND INCOMPLETE DATA"

ATENÇÃO! VAGAS LIMITADAS! NÃO PERCA ESTA OPORTUNIDADE E FAÇA HOJE MESMO A
SUA INSCRIÇÃO!

*PERÍODO E HORÁRIO: *12 a 16 de novembro de 2018, das 09 ás 12h e das 14 ás
17h

*LOCAL: *Departamento de Ciências Exatas, Prédio da Engenharia, ESALQ/USP, Sala
315, na Avenida P
<https://maps.google.com/?q=Avenida+P+dua+Dias,+11&entry=gmail&source=g>ádua
Dias, 11
<https://maps.google.com/?q=Avenida+P+dua+Dias,+11&entry=gmail&source=g>,
em Piracicaba, SP

*OBJETIVO: *Esse workshop discutirá temas atuais e muito importantes dentro
da Estatística, envolvendo modelos lineares mistos, e trará grandes
contribuições para nossos alunos e profissionais em geral da área de
Estatística

*COORDENADORA: *Prof.ª Dr.ª Clarice Garcia Borges Demétrio (ESALQ/USP)

*PALESTRANTE: *Geert Molenberghs (50%), I-BioStat, UHasselt & K.U.Leuven

*Abstract: *First present linear mixed models for continuous hierarchical
data. The focus lies on the modeler’s perspective and on applications.
Emphasis will be on model formulation, parameter estimation, and hypothesis
testing, as well as on the distinction between the random-effects
(hierarchical) model and the implied marginal model. Apart from classical
model building strategies, many of which have been implemented in standard
statistical software, a number of flexible extensions and additional tools
for model diagnosis will be indicated. Second, models for non-Gaussian data
will be discussed, with a strong emphasis on generalized estimating
equations (GEE) and the generalized linear mixed model (GLMM). To usefully
introduce this theme, a brief review of the classical generalized linear
modeling framework will be presented. Similarities and differences with the
continuous case will be discussed. The differences between marginal models,
such as GEE, and random-effects models, such as the GLMM, will be explained
in detail. Third, when analysing hierarchical and longitudinal data, one is
often confronted with missing observations, i.e., scheduled measurements
have not been made, due to a variety of (known or unknown) reasons. It will
be shown that, if no appropriate measures are taken, missing data can cause
seriously jeopardize results, and interpretational difficulties are bound
to occur. Methods to properly analyze incomplete data, under flexible
assumptions, are presented. Key concepts of sensitivity analysis are
introduced. Throughout the workshop, it will be assumed that the
participants are familiar with basic statistical modelling, including
linear models (regression and analysis of variance), as well as generalized
linear models (logistic and Poisson regression). Moreover, pre-requisite
knowledge should also include general estimation and testing theory
(maximum likelihood, likelihood ratio). All developments will be
illustrated with worked examples using the SAS System. These will be
supplemented with practical sessions.

*Presenter: *Geert Molenberghs is Professor of Biostatistics at the
Universiteit Hasselt and the Katholieke Universiteit Leuven in Belgium. He
received the B.S. degree in mathematics (1988) and a Ph.D. in biostatistics
(1993) from the Universiteit Antwerpen. Dr Molenberghs published
methodological work on surrogate markers in clinical trials, categorical
data, longitudinal data analysis, and on the analysis of non-response in
clinical and epidemiological studies. He served as Joint Editor for Applied
Statistics (2001-2004) and is President of the International Biometric
Society (2004-2005). He was elected Fellow of the American Statistical
Association and received the Guy Medal in Bronze from the Royal Statistical
Society. He has held visiting positions at the Harvard School of Public
Health (Boston, MA). He is currently Co-Editor of Biometrics (2007–2009).

Both presenters are editor and author of four books on the use of linear
mixed models for the analysis of longitudinal data (Springer Lecture Notes
1997, Springer Series in Statistics 2000, Springer Series in Statistics
2005, Chapman & Hall/CRC 2009), and they have taught numerous short and
longer courses on the topic in universities as well as industry, in Europe,
North America, Latin America, and Australia.

*Materials*: Copies of the transparencies used.

*CARGAS HORÁRIA: *30h

*NÚMERO DE VAGAS: 4*0

*TAXA DE INSCRIÇÃO*

Profissional - R$ 300,00

Estudante - R$ 150,00

*ATENÇÃO:* A VAGA FICARÁ GARANTIDA POR 5 DIAS, CONTADOS A PARTIR DA DATA DA
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