Abstract
This work focuses on the development of a framework that implements computer intensive methods for mixed-effects models in an easy and efficient way, and special attention is given to flexible bootstrap techniques. Here we developed an S-Plus library, nlme.bootstrap, as an extension of the standard nlme library in S. This new library is designed for Monte Carlo and bootstrap methods for mixed-effects models. Some design and implementation aspects are described. To illustrate the use of the software, a simulation study on the performance of parametric bootstrap in the presence of non-normality is discussed.
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References
Davison A, Hinkley D (1997). Bootstrap Methods and their application. Cambridge: Cambridge Ufiiversity Press.
Goldstein H. (1987) Multilevel Models in Educational and Social Research. London: Griffin.
Pinheiro, J.C. Bates D. (2000). Mixed-Effects Models in S and S-Plus. New York: Springer-Verlag.
Verbeke G, Molenberghs G (1997) Linear Mixed Models in Practice: A SAS oriented approach. Lecture Notes in Statistics 126. New York: Springer-Verlag.
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© 2002 Springer-Verlag Berlin Heidelberg
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Sanchez, J.A., Ocaña, J. (2002). Computer Intensive Methods for Mixed-effects Models. In: Härdle, W., Rönz, B. (eds) Compstat. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57489-4_36
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DOI: https://doi.org/10.1007/978-3-642-57489-4_36
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1517-7
Online ISBN: 978-3-642-57489-4
eBook Packages: Springer Book Archive