[ABE-L] Seminários em Estatística e Ciência de Dados - Departamento de Estatística da UFBA

[Paulo C Rodrigues]

Prezados Colegas,

Na próxima terça-feira, dia* 16 de novembro, às 18h00*, vamos dar
continuidade aos Seminários em Estatística e Ciência de Dados da
Universidade Federal da Bahia.

Este seminário será ministrado pelo *Professor Daniel Jeske*, do Department
of Statistics, University of California, Riverside, USA.

Daniel Jeske is a Professor in the department of statistics at the
University of California, Riverside (USA), where he served as the
department chair during 2008-2015.  He is also a Vice-Provost of Academic
Personnel at UCR, and previously was Vice Provost of Administrative
Resolution.  He is an elected fellow of the American Statistical
Association and served on the board of directors during 2014-2016  He is
the current President for the International Society of Business and
Industrial Statistics (ISBIS), a society of the International Statistical
Institute (ISI).  He is the past Editor-in-Chief of The American
Statistician.  His research interests include classification and prediction
methodologies, statistical process control methodologies, biostatistics
applications, and reliability modeling.


Os detalhes do seminários são os seguintes:

====================================================
*Title*: Sample size calculations for mixture alternatives in a control
group vs. treatment group design

*Abstract*: We consider a control group versus treatment group experimental
design and assert that powering the design for a potential treatment effect
that is represented by a pure shift of the control group distribution is
usually unrealistic. Instead, we propose the use of a mixture model as the
design alternative in anticipation that there might be a sub-population in
the treated population whose responses come from the same control group
distribution. When the responses in the treatment group follow a mixture
model, the sample size found by the traditional pure shift alternative
based method is demonstrated to be underpowered. We develop a new sample
size formula for the Wilcoxon test statistic and propose a more general
definition of the treatment effect. Method of moment estimators of the
treatment effect are proposed and their bias and mean squared error
properties are evaluated. [Joint work with Bradley Lubich and Weixin Yao]

*Data*: 18h00 do dia 16 de novembro de 2021

*Transmissão ao vivo online em*: https://meet.google.com/ssj-cdnb-nbo

====================================================

Partilhem com os vossos colegas!

São todos bem-vindos!

Um abraço,
Paulo Canas Rodrigues
Paulo Henrique Ferreira

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Paulo Canas Rodrigues
*Professor* at Federal University of Bahia <http://ufba.br>, Brazil
*President*, Brazilian Region of the International Biometric Society
<http://www.rbras.org.br>
*President-Elect, International Society for Business and
<https://www.isbis-isi.org/>**Industrial* *Statistics*
<https://www.isbis-isi.org/>
*(Founding) Chair,SIG on Data Science, of the International Statistical
Institute <https://www.isi-web.org/>*
*Vice-Coordinator*, Specialization in Data Science and Big Data
<http://ecd.ufba.br>
*Member of the Board of Directors, *Brazilian Statistical Association
<https://www.redeabe.org.br/>
*Editor for*: CompStat <https://www.springer.com/journal/180>, SOIC
<http://www.iapress.org/index.php/soic>, Biom. Letters
<http://www.up.poznan.pl/biometrical.letters/>, Rev.Bras.Biom.
<http://www.biometria.ufla.br/index.php/BBJ>

*CV Lattes*: http://lattes.cnpq.br/0029960374321970
*Web*: www.paulocanas.org
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