Course detail

LCE5872 - Experimental Statistics II and Mixed Models

Credit hours

In-class work
per week
per week
15 weeks
120 hours

Clarice Garcia Borges Demetrio
Sonia Maria de Stefano Piedade
Taciana Villela Savian

Aims to provide a solid methodological basis for the use of models in the analysis of continuous data and in research, involving concepts of matrix algebra and statistical inference, teaching Hasse diagrams, linear models for incomplete data using the theory of mixed models, including the estimation techniques, checking of model fitting, diagnostics, inference and confidence intervals.

Hasse Diagrams. Unbalanced cross-classifications. Split-plot experiments. Split-Block experiments. Incomplete block designs. Lattice squares. Groups of experiments. Groups of experiments with common treatments (augmented block). Introduction to mixed models.

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. (ISBN-13: 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.
Wu, L. (2009). Mixed effects models for complex data. Chapman and Hall/CRC. 431p. (ISBN-13: 978-1420074024).