The nonlinear mixed effects model with a smooth random effects density

Published

Journal Article

SUMMARY: The fixed parameters of the nonlinear mixed effects model and the density of the random effects are estimated jointly by maximum likelihood. The density of the random effects is assumed to be smooth but is otherwise unrestricted. The method uses a series expansion that follows from the smoothness assumption to represent the density and quadrature to compute the likelihood. Standard algorithms are used for optimization. Empirical Bayes estimates of random coefficients are obtained by computing posterior modes. The method is applied to data from pharmacokinetics, and properties of the method are investigated by application to simulated data. © 1993 Biometrika Trust.

Full Text

Duke Authors

Cited Authors

  • Davidian, M; Gallant, AR

Published Date

  • September 1, 1993

Published In

Volume / Issue

  • 80 / 3

Start / End Page

  • 475 - 488

International Standard Serial Number (ISSN)

  • 0006-3444

Digital Object Identifier (DOI)

  • 10.1093/biomet/80.3.475

Citation Source

  • Scopus