GLMMadaptive: Generalized Linear Mixed Models using Adaptive Gaussian...

Description Details Author(s) References See Also

Description

This package fits generalized linear mixed models for a single grouping factor under maximum likelihood approximating the integrals over the random effects with an adaptive Gaussian quadrature rule.

Details

Package: GLMMadaptive
Type: Package
Version: 0.5-1
Date: 2019-01-28
License: GPL (>=3)

This package fits mixed effects models for grouped / repeated measurements data for which the integral over the random effects in the definition of the marginal likelihood cannot be solved analytically. The package approximates these integrals using the adaptive Gauss-Hermite quadrature rule.

Multiple random effects terms can be included for the grouping factor (e.g., random intercepts, random linear slopes, random quadratic slopes), but currently only a single grouping factor is allowed.

The package also offers several utility functions that can extract useful information from fitted mixed effects models. The most important of those are included in the See also Section below.

Author(s)

Dimitris Rizopoulos

Maintainer: Dimitris Rizopoulos <[email protected]>

References

Fitzmaurice, G., Laird, N. and Ware J. (2011). Applied Longitudinal Analysis, 2nd Ed. New York: John Wiley & Sons.

Molenberghs, G. and Verbeke, G. (2005). Models for Discrete Longitudinal Data. New York: Springer-Verlag.

See Also

mixed_model, methods.MixMod, effectPlotData, marginal_coefs


GLMMadaptive documentation built on May 2, 2019, 2:51 p.m.