Disciplina - detalhe

LCE5872 - Estatística Experimental II e Modelos Mistos


Carga Horária

Teórica
por semana
Prática
por semana
Créditos
Duração
Total
3
1
8
15 semanas
120 horas

Docentes responsáveis
Clarice Garcia Borges Demetrio
Renata Alcarde Sermarini
Sonia Maria de Stefano Piedade
Taciana Villela Savian

Objetivo
Fornecer ao aluno uma base sólida metodológica para a análise de dados contínuos em pesquisa
experimental, incluindo o uso de diagramas de Hasse e modelos mitosos para dados incompletos.

Conteúdo
Ementa:
Definição e formulação de modelos envolvendo conceitos de álgebra matricial e inferência estatística
para a análise de dados contínuos, usando diagramas de Hasse, dando ênfase a modelos lineares para
dados incompletos, usando a teoria de modelos mistos, incluindo as técnicas de estimação, de
verificação de ajuste dos modelos e de diagnósticos. Todos os métodos e aplicações usarão o software
R.
Conteúdo:
1. Diagramas de Hasse.
2. Introdução aos modelos mistos.
3. Classificações cruzadas desbalanceadas.
4. Experimentos em parcelas subdivididas .
5. Experimentos em faixas.
6. Blocos Incompletos balanceados.
7. Reticulados Quadrados.
8. Análise conjunta de grupos de Experimentos.
9. Análise conjunta de grupos de experimentos com tratamentos comuns (Blocos aumentados).

Bibliografia
Bailey, R. A. (2008). Design of Comparative Experiments. Cambridge, Cambridge University Press.
348p. ( ISBN-13: 9780521683579)
Box, G.E.P.; Hunter, W.G.; Hunter, J.S. (2005). Statistics for experimenters:Design, Innovation, and
Discovery. 2nd Edition. Wiley, New York. 664p. (ISBN-13: 978-0471718130)
Casella, G. (2010). Statistical Design. New York, Springer. 330p. ( ISBN-13: 978-1441926142)
Cochran, W.G. and Cox, G.M. (1992). Experimental designs. 2nd Edition. Wiley, New York. 640p. (
ISBN-13: 978-0471545675)
Cox, D.R.; Donnelly, C.A. (2011). Principles of Applied Statistical. Cambridge, Cambridge University
Press. 212p. (ISBN: 9781107644458)
Davis, C. S. (2010). Statistical Methods for the Analysis of Repeated Measurements. Springer Texts in
Statistics. 439p. (ISBN-13: 978-1441929761)
Demidenko, E. (2004). Mixed Models: Theory and Applications. New Jersey, Wiley. 736p. (ISBN-13:
978-0471601616)
Dey, A. (2010). Incomplete Block Design. World Scientific Publishing Company. 1 edition. 288p. (ISBN13: 978-9814322683)
Federer, W.T. (1993). Statistical design and analysis for intercropping experiments. Springer-Verlag.
New York.298p. ( ISBN-13: 978-0387979236)
Fitzmaurice; G. M.; Laird, N. M.; Ware, J. H. (2004). Applied Longitudinal Analysis. Wiley Series in
Probability and Statistics. 536p. (ISBN-13: 978-0471214878)
Galwey, N. W. (2006) Introduction to Mixed Modelling: Beyond Regression and Analysis of Variance.
Chichester, Wiley. 376p. (ISBN-13: 978-0470014967)
Lawson, J. (2010). Design and Analysis of Experiments with SAS. Chapman & Hall/CRC Texts in
Statistical Science. 596p. (ISBN-13: 978-1420060607)
McCulloch, C.E.; Searle, S. R.; Neuhaus, J.M. (2008). Generalized, Linear, and Mixed Models. Wiley
Series in Probability and Statistics. 424p. (ISBN-13: 978-0470073711)
Mead, R.; Curnow, R.N.; Hasted, A. M.; Curnow, R.M. (2002). Statistical Methods in Agriculture and
Experimental Biology, 3th Edition. Champman & Hall/CRC, USA., 488 p. (ISBN-13: 978-1584881872)
Milliken, G.A.; Johnson, D.E. (2004). Analysis of messy data. Vol I : Designed of experiments.
Chapmann Hall. London. 674p. (ISBN-13: 978-1584883340)
Montgomery, D.C. (2008). Design and analysis of experiments. 7th Edition. Wiley, New York. 680p.
(ISBN-13: 978-0470128664)
Morris, M. (2010). Design of Experiments: An Introduction Based on Linear Models. Chapman &
Hall/CRC Texts in Statistical Science. 370p. (ISBN-13: 978-1584889236)
Pinheiro, J. C.; Bates, D. M. (2009). Mixed-effects models in S and S-PLUS. New York, Springer. 548p. (
ISBN-13: 978-1441903174)
Ryan, T. P. (2007). Modern experimental design. Hoboken, N.J., Wiley-Interscience. 593p. (ISBN-13:
978-0471210771).
Searle, S.R.; Casella, G.; McCulloch, C.E. (2006).Variance components. John Wiley & Sons, Inc.. New York. 536p. (ISBN-13: 978-0470009598).
Venables, W.N. and Ripley, B.D. (2010). Modern applied statistics with S: Statistics and Computing.
Springer, New York. 506p. (ISBN-13: 978-1441930088)
Verbeke, G.; Molenberghs, G. (2009). Linear Mixed Models for Longitudinal Data. Springer Series in
Statistics. 592p. (ISBN-13: 978-1441902993)
Welham, S.J.; Gezan, S.A.; Clark, S.J.; Mead; A. (2014) Statistical Methods in Biology. Design and
Analysis of Experiments and Regression. CRC Press.
WEST, B.; WELCH, K.B; GALECKI, A.T. (2014). Linear Mixed Models: A Practical Guide Using Statistical
Software. 2ª ed. Chapman & Hall/CRC.
Wu, L. (2009). Mixed effects models for complex data. Chapman and Hall/CRC. 431p. (ISBN-13: 978-
1420074024).